diff --git a/closed/MLCommons/systems/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config.json b/closed/MLCommons/systems/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config.json index 77475211f..b71e8eae9 100644 --- a/closed/MLCommons/systems/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config.json +++ b/closed/MLCommons/systems/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config.json @@ -1,9 +1,9 @@ { - "accelerator_frequency": "2520000 MHz", + "accelerator_frequency": "2610000 MHz", "accelerator_host_interconnect": "N/A", "accelerator_interconnect": "N/A", "accelerator_interconnect_topology": "", - "accelerator_memory_capacity": "23.64971923828125 GB", + "accelerator_memory_capacity": "23.54595947265625 GB", "accelerator_memory_configuration": "N/A", "accelerator_model_name": "NVIDIA GeForce RTX 4090", "accelerator_on-chip_memories": "", @@ -16,17 +16,17 @@ "host_network_card_count": "1", "host_networking": "Gig Ethernet", "host_networking_topology": "N/A", - "host_processor_caches": "L1d cache: 576 KiB, L1i cache: 384 KiB, L2 cache: 24 MiB, L3 cache: ", - "host_processor_core_count": "24", - "host_processor_frequency": "5800.0000", + "host_processor_caches": "L1d cache: 512 KiB, L1i cache: 512 KiB, L2 cache: 16 MiB, L3 cache: 64 MiB", + "host_processor_core_count": "16", + "host_processor_frequency": "5881.0000", "host_processor_interconnect": "", - "host_processor_model_name": "13th Gen Intel(R) Core(TM) i9-13900K", + "host_processor_model_name": "AMD Ryzen 9 7950X 16-Core Processor", "host_processors_per_node": "1", - "host_storage_capacity": "9.4T", + "host_storage_capacity": "6.8T", "host_storage_type": "SSD", "hw_notes": "", "number_of_nodes": "1", - "operating_system": "Ubuntu 20.04 (linux-6.8.0-49-generic-glibc2.31)", + "operating_system": "Ubuntu 20.04 (linux-6.8.0-51-generic-glibc2.31)", "other_software_stack": "Python: 3.8.10, GCC-9.4.0, Using Docker , CUDA 12.2", "status": "available", "submitter": "MLCommons", diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/README.md b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/README.md index 4d6a2a991..ad62f33c0 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/README.md +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/README.md @@ -1,5 +1,3 @@ -This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). - *Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* ## Host platform @@ -19,7 +17,7 @@ pip install -U cmind cm rm cache -f -cm pull repo mlcommons@mlperf-automations --checkout=a90475d2de72bf0622cebe8d5ca8eb8c9d872fbd +cm pull repo mlcommons@mlperf-automations --checkout=48ea6b46a7606d1c5d74909e94d5599dbe7ff9e1 cm run script \ --tags=app,mlperf,inference,generic,_nvidia,_resnet50,_tensorrt,_cuda,_valid,_r4.1-dev_default,_multistream \ @@ -41,8 +39,8 @@ cm run script \ --env.CM_RUN_MLPERF_SUBMISSION_PREPROCESSOR=yes \ --env.CM_MLPERF_INFERENCE_PULL_CODE_CHANGES=yes \ --env.CM_MLPERF_INFERENCE_PULL_SRC_CHANGES=yes \ - --env.OUTPUT_BASE_DIR=/home/arjun/gh_action_results \ - --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/gh_action_submissions \ + --env.OUTPUT_BASE_DIR=/cm-mount/home/arjun/gh_action_results \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/cm-mount/home/arjun/gh_action_submissions \ --env.CM_MLPERF_SUBMITTER=MLCommons \ --env.CM_USE_DATASET_FROM_HOST=yes \ --env.CM_USE_MODEL_FROM_HOST=yes \ @@ -71,7 +69,7 @@ cm run script \ --env.CM_DOCKER_REUSE_EXISTING_CONTAINER=yes \ --env.CM_DOCKER_DETACHED_MODE=yes \ --env.CM_MLPERF_INFERENCE_RESULTS_DIR_=/home/arjun/gh_action_results/valid_results \ - --env.CM_DOCKER_CONTAINER_ID=2a6a3464ad42 \ + --env.CM_DOCKER_CONTAINER_ID=bec71595fc42 \ --env.CM_MLPERF_LOADGEN_COMPLIANCE_TEST=TEST04 \ --add_deps_recursive.compiler.tags=gcc \ --add_deps_recursive.coco2014-original.tags=_full \ @@ -104,11 +102,7 @@ cm run script \ --v=False \ --print_env=False \ --print_deps=False \ - --dump_version_info=True \ - --env.CM_DATASET_IMAGENET_PATH=/home/cmuser/CM/repos/local/cache/14a94e79cca24141/imagenet-2012-val \ - --env.OUTPUT_BASE_DIR=/cm-mount/home/arjun/gh_action_results \ - --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/cm-mount/home/arjun/gh_action_submissions \ - --env.MLPERF_SCRATCH_PATH=/home/cmuser/CM/repos/local/cache/a8c152aef5494496 + --dump_version_info=True ``` *Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), you should simply reload mlcommons@mlperf-automations without checkout and clean CM cache as follows:* @@ -130,4 +124,4 @@ Model Precision: int8 `acc`: `76.064`, Required accuracy for closed division `>= 75.6954` ### Performance Results -`Samples per query`: `457694.0` +`Samples per query`: `798611.0` diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/accuracy_console.out b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/accuracy_console.out index f167561e2..138d196e8 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/accuracy_console.out +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/accuracy_console.out @@ -1,7 +1,7 @@ -[2024-12-25 00:37:31,507 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 -[2024-12-25 00:37:31,677 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/MultiStream -[2024-12-25 00:37:31,677 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="AccuracyOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=8 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/f4e208664f514db1b83009a13b96a25a.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/MultiStream/resnet50-MultiStream-gpu-b8-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario MultiStream --model resnet50 -[2024-12-25 00:37:31,677 __init__.py:53 INFO] Overriding Environment +[2025-01-01 09:51:03,848 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 +[2025-01-01 09:51:04,021 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/MultiStream +[2025-01-01 09:51:04,021 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="AccuracyOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=8 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/1fbc7af38b044fecb562b377ad90de53.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/MultiStream/resnet50-MultiStream-gpu-b8-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario MultiStream --model resnet50 +[2025-01-01 09:51:04,021 __init__.py:53 INFO] Overriding Environment benchmark : Benchmark.ResNet50 buffer_manager_thread_count : 0 data_dir : /home/cmuser/CM/repos/local/cache/a8c152aef5494496/data @@ -11,7 +11,7 @@ gpu_copy_streams : 1 gpu_inference_streams : 1 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2024.12.25-00.37.30 +log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2025.01.01-09.51.02 map_path : data_maps/imagenet/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf multi_stream_expected_latency_ns : 0 @@ -25,7 +25,7 @@ tensor_path : build/preprocessed_data/imagenet/ResNet50/int8_linear test_mode : AccuracyOnly use_deque_limit : True use_graphs : True -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/f4e208664f514db1b83009a13b96a25a.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/1fbc7af38b044fecb562b377ad90de53.conf system_id : RTX4090x1 config_name : RTX4090x1_resnet50_MultiStream workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -39,7 +39,7 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/f4e208664f514db1b83009a13b96a25a.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/1fbc7af38b044fecb562b377ad90de53.conf Creating QSL. Finished Creating QSL. Setting up SUT. @@ -58,7 +58,7 @@ Setting up SUT. [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.02414s. +Finished warmup. Ran for 5.02403s. Starting running actual test. No warnings encountered during test. @@ -71,8 +71,8 @@ Device Device:0.GPU processed: PerSampleCudaMemcpy Calls: 0 BatchedCudaMemcpy Calls: 6250 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-25 00:37:45,065 run_harness.py:166 INFO] Result: Accuracy run detected. -[2024-12-25 00:37:45,065 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-imagenet.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/accuracy/mlperf_log_accuracy.json --imagenet-val-file data_maps/imagenet/val_map.txt --dtype int32 +[2025-01-01 09:51:46,180 run_harness.py:166 INFO] Result: Accuracy run detected. +[2025-01-01 09:51:46,180 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-imagenet.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/accuracy/mlperf_log_accuracy.json --imagenet-val-file data_maps/imagenet/val_map.txt --dtype int32 accuracy=76.064%, good=38032, total=50000 ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/cm-deps.mmd b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/cm-deps.mmd index 8c84897bc..9d2be6862 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/cm-deps.mmd +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/cm-deps.mmd @@ -15,19 +15,19 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_package.numpy_) --> get,python3 get-cuda-devices,7a3ede4d3558427a_(_with-pycuda_) --> get,generic-python-lib,_package.numpy app-mlperf-inference,d775cac873ee4231_(_nvidia,_resnet50,_tensorrt,_cuda,_valid,_r4.1-dev_default,_multistream_) --> get,cuda-devices,_with-pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,dataset,original,imagenet,_full - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,dataset,original,imagenet,_full + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> pull,git,repo generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,os detect-cpu,586c8a43320142f7 --> detect,os generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,cpu @@ -35,45 +35,45 @@ graph TD generate-mlperf-inference-user-conf,3af4475745964b93 --> get,mlcommons,inference,src get-mlperf-inference-sut-configs,c2fbf72009e2445b --> get,cache,dir,_name.mlperf-inference-sut-configs generate-mlperf-inference-user-conf,3af4475745964b93 --> get,sut,configs - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> generate,user-conf,mlperf,inference + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> generate,user-conf,mlperf,inference get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,dataset,original,imagenet,_full - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,dataset,original,imagenet,_full + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_cuda,_resnet50,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_resnet50,_cuda,_tensorrt,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> get,generic-python-lib,_package.onnx - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_cuda,_resnet50,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_resnet50,_cuda,_tensorrt,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> get,generic-python-lib,_package.onnx detect-cpu,586c8a43320142f7 --> detect,os benchmark-program,19f369ef47084895 --> detect,cpu benchmark-program-mlperf,cfff0132a8aa4018 --> benchmark-program,program - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/cm-deps.png b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/cm-deps.png index 86aeb44cb..68d1547a2 100644 Binary files a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/cm-deps.png and b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/cm-deps.png differ diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/cm-version-info.json b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/cm-version-info.json index 09af87063..147fc9708 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/cm-version-info.json +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/cm-version-info.json @@ -167,7 +167,7 @@ "script_tags": "detect-os,detect,os,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -187,7 +187,7 @@ "script_tags": "detect,cpu,detect-cpu,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -197,7 +197,7 @@ "script_tags": "get,sys-utils-cm", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -207,7 +207,7 @@ "script_tags": "get,mlperf,inference,nvidia,scratch,space", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -227,7 +227,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "mlperf_logging", "version": "4.1.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -237,7 +237,7 @@ "script_tags": "get,val,validation,dataset,imagenet,ILSVRC,image-classification,original", "script_variations": "full", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -247,7 +247,7 @@ "script_tags": "get,raw,ml-model,resnet50,ml-model-resnet50,image-classification", "script_variations": "fp32,onnx,opset-8", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -257,7 +257,7 @@ "script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons", "script_variations": "", "version": "master-git-2fdb814e6a765d994872fb99ee38f8c43418d5b0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -267,7 +267,7 @@ "script_tags": "get,nvidia,mlperf,inference,common-code", "script_variations": "mlcommons", "version": "r4.0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -287,7 +287,7 @@ "script_tags": "pull,git,repo,repository", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -367,7 +367,7 @@ "script_tags": "generate,mlperf,inference,user-conf,inference-user-conf", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -387,7 +387,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.pycuda", "version": "2022.2.2", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -397,7 +397,7 @@ "script_tags": "get,nvidia,mitten,nvidia-mitten", "script_variations": "", "version": "master", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -407,7 +407,7 @@ "script_tags": "get,cuda,cuda-compiler,cuda-lib,toolkit,lib,nvcc,get-nvcc,get-cuda,46d133d9ef92422d", "script_variations": "cudnn", "version": "12.2", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -417,7 +417,7 @@ "script_tags": "get,tensorrt,nvidia", "script_variations": "", "version": "vdetected", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -427,7 +427,7 @@ "script_tags": "build,mlcommons,mlperf,inference,inference-server,server,nvidia-harness,nvidia", "script_variations": "mlcommons", "version": "r4.0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -437,7 +437,7 @@ "script_tags": "detect-os,detect,os,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8 )" } }, { @@ -457,7 +457,7 @@ "script_tags": "detect,cpu,detect-cpu,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8 )" } }, { @@ -467,7 +467,7 @@ "script_tags": "get,sys-utils-cm", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8 )" } }, { @@ -477,7 +477,7 @@ "script_tags": "get,mlperf,inference,nvidia,scratch,space", "script_variations": "version.4_0", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8 )" } }, { @@ -497,7 +497,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "mlperf_logging", "version": "4.1.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8 )" } }, { @@ -507,7 +507,7 @@ "script_tags": "get,val,validation,dataset,imagenet,ILSVRC,image-classification,original", "script_variations": "full", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8 )" } }, { @@ -517,7 +517,7 @@ "script_tags": "get,raw,ml-model,resnet50,ml-model-resnet50,image-classification", "script_variations": "fp32,onnx,opset-8", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8 )" } }, { @@ -527,7 +527,7 @@ "script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons", "script_variations": "", "version": "master-git-2fdb814e6a765d994872fb99ee38f8c43418d5b0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8 )" } }, { @@ -537,7 +537,7 @@ "script_tags": "get,nvidia,mlperf,inference,common-code", "script_variations": "mlcommons", "version": "r4.0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8 )" } }, { @@ -557,7 +557,7 @@ "script_tags": "pull,git,repo,repository", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8 )" + 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{ @@ -677,27 +677,27 @@ "script_tags": "save,mlperf,inference,implementation,state", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8 )" } }, { - "reproduce,mlperf,inference,nvidia,harness,_build_engine,_tensorrt,_cuda,_resnet50,_multistream,_v4.1-dev,_batch_size.8": { + "reproduce,mlperf,inference,nvidia,harness,_build_engine,_resnet50,_cuda,_multistream,_tensorrt,_v4.1-dev,_batch_size.8": { "script_uid": "bc3b17fb430f4732", "script_alias": "app-mlperf-inference-nvidia", "script_tags": "reproduce,mlcommons,mlperf,inference,harness,nvidia-harness,nvidia", - "script_variations": "build_engine,tensorrt,cuda,resnet50,multistream,v4.1-dev,batch_size.8", + "script_variations": 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+ "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -717,7 +717,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "onnx-graphsurgeon", "version": "0.3.27", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -737,7 +737,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.onnx", "version": "1.13.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } }, { @@ -777,7 +777,7 @@ "script_tags": "mlperf,benchmark-mlperf", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_resnet50,_multistream,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_cuda,_multistream,_tensorrt,_rtx_4090 )" } } ] diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/os_info.json b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/os_info.json index 834f81f03..36b84384c 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/os_info.json +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/os_info.json @@ -26,5 +26,5 @@ ], "CM_HOST_PLATFORM_FLAVOR": "x86_64", "CM_HOST_PYTHON_BITS": "64", - "CM_HOST_SYSTEM_NAME": "2a6a3464ad42" + "CM_HOST_SYSTEM_NAME": "bec71595fc42" } \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/performance_console.out b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/performance_console.out index 9af94bf00..93a5cfbe8 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/performance_console.out +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/performance_console.out @@ -1,7 +1,7 @@ -[2024-12-25 00:27:12,401 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 -[2024-12-25 00:27:12,572 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/MultiStream -[2024-12-25 00:27:12,572 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="PerformanceOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=8 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/fdf941e1b44d476d84f19f0ead7880e1.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/MultiStream/resnet50-MultiStream-gpu-b8-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario MultiStream --model resnet50 -[2024-12-25 00:27:12,573 __init__.py:53 INFO] Overriding Environment +[2025-01-01 09:40:26,295 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 +[2025-01-01 09:40:26,455 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/MultiStream +[2025-01-01 09:40:26,455 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="PerformanceOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=8 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/a0f650b7d6b14b13a48094819b58e5f4.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/MultiStream/resnet50-MultiStream-gpu-b8-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario MultiStream --model resnet50 +[2025-01-01 09:40:26,455 __init__.py:53 INFO] Overriding Environment benchmark : Benchmark.ResNet50 buffer_manager_thread_count : 0 data_dir : /home/cmuser/CM/repos/local/cache/a8c152aef5494496/data @@ -11,7 +11,7 @@ gpu_copy_streams : 1 gpu_inference_streams : 1 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2024.12.25-00.27.11 +log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2025.01.01-09.40.25 map_path : data_maps/imagenet/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf multi_stream_expected_latency_ns : 0 @@ -25,7 +25,7 @@ tensor_path : build/preprocessed_data/imagenet/ResNet50/int8_linear test_mode : PerformanceOnly use_deque_limit : True use_graphs : True -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/fdf941e1b44d476d84f19f0ead7880e1.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/a0f650b7d6b14b13a48094819b58e5f4.conf system_id : RTX4090x1 config_name : RTX4090x1_resnet50_MultiStream workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -39,7 +39,7 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/fdf941e1b44d476d84f19f0ead7880e1.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/a0f650b7d6b14b13a48094819b58e5f4.conf Creating QSL. Finished Creating QSL. Setting up SUT. @@ -58,7 +58,7 @@ Setting up SUT. [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.02408s. +Finished warmup. Ran for 5.02391s. Starting running actual test. ================================================ MLPerf Results Summary @@ -66,29 +66,29 @@ MLPerf Results Summary SUT name : LWIS_Server Scenario : MultiStream Mode : PerformanceOnly -99th percentile latency (ns) : 457564 +99th percentile latency (ns) : 790777 Result is : VALID Min duration satisfied : Yes Min queries satisfied : Yes Early stopping satisfied: Yes Early Stopping Result: - * Processed at least 662 queries (1336340). - * Would discard 13095 highest latency queries. - * Early stopping 99th percentile estimate: 457694 + * Processed at least 662 queries (1272080). + * Would discard 12458 highest latency queries. + * Early stopping 99th percentile estimate: 798611 ================================================ Additional Stats ================================================ Per-query latency: -Min latency (ns) : 433289 -Max latency (ns) : 1487258 -Mean latency (ns) : 444464 -50.00 percentile latency (ns) : 443509 -90.00 percentile latency (ns) : 449059 -95.00 percentile latency (ns) : 451323 -97.00 percentile latency (ns) : 453617 -99.00 percentile latency (ns) : 457564 -99.90 percentile latency (ns) : 465790 +Min latency (ns) : 430884 +Max latency (ns) : 357813780 +Mean latency (ns) : 465760 +50.00 percentile latency (ns) : 446123 +90.00 percentile latency (ns) : 475468 +95.00 percentile latency (ns) : 494413 +97.00 percentile latency (ns) : 551560 +99.00 percentile latency (ns) : 790777 +99.90 percentile latency (ns) : 2956252 ================================================ Test Parameters Used @@ -118,12 +118,12 @@ No warnings encountered during test. No errors encountered during test. Finished running actual test. Device Device:0.GPU processed: - 1336340 batches of size 8 + 1272080 batches of size 8 Memcpy Calls: 0 PerSampleCudaMemcpy Calls: 0 - BatchedCudaMemcpy Calls: 1336340 + BatchedCudaMemcpy Calls: 1272080 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-25 00:37:20,895 run_harness.py:166 INFO] Result: result_99.00_percentile_per_query_latency_ns: 457564, Result is VALID +[2025-01-01 09:50:45,572 run_harness.py:166 INFO] Result: result_99.00_percentile_per_query_latency_ns: 790777, Result is VALID ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/system_info.txt b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/system_info.txt index 39b2ab1a8..00ee5a21d 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/system_info.txt +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/system_info.txt @@ -2,10 +2,10 @@ Platform Details ------------------------------------------------------------ 1. uname -a -Linux 2a6a3464ad42 6.8.0-51-generic #52-Ubuntu SMP PREEMPT_DYNAMIC Thu Dec 5 13:09:44 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux +Linux bec71595fc42 6.8.0-51-generic #52-Ubuntu SMP PREEMPT_DYNAMIC Thu Dec 5 13:09:44 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux ------------------------------------------------------------ 2. w - 00:37:22 up 6 days, 10:30, 0 users, load average: 1.01, 1.02, 1.00 + 09:50:53 up 13 days, 19:43, 0 users, load average: 8.35, 9.50, 16.06 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT ------------------------------------------------------------ 3. Username @@ -40,7 +40,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 3226.111 cache size : 1024 KB physical id : 0 siblings : 32 @@ -96,7 +96,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5489.211 +cpu MHz : 5476.790 cache size : 1024 KB physical id : 0 siblings : 32 @@ -124,7 +124,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5488.645 cache size : 1024 KB physical id : 0 siblings : 32 @@ -152,7 +152,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5486.737 cache size : 1024 KB physical id : 0 siblings : 32 @@ -180,7 +180,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5397.675 +cpu MHz : 5489.475 cache size : 1024 KB physical id : 0 siblings : 32 @@ -236,7 +236,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5126.050 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -264,7 +264,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5262.304 +cpu MHz : 5209.237 cache size : 1024 KB physical id : 0 siblings : 32 @@ -292,7 +292,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5202.496 cache size : 1024 KB physical id : 0 siblings : 32 @@ -348,7 +348,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 3640.092 +cpu MHz : 5286.767 cache size : 1024 KB physical id : 0 siblings : 32 @@ -376,7 +376,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 3530.331 cache size : 1024 KB physical id : 0 siblings : 32 @@ -404,7 +404,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4237.595 cache size : 1024 KB physical id : 0 siblings : 32 @@ -432,7 +432,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5239.853 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -488,7 +488,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5402.497 cache size : 1024 KB physical id : 0 siblings : 32 @@ -516,7 +516,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5461.655 cache size : 1024 KB physical id : 0 siblings : 32 @@ -544,7 +544,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5386.313 +cpu MHz : 5483.904 cache size : 1024 KB physical id : 0 siblings : 32 @@ -600,7 +600,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5487.854 cache size : 1024 KB physical id : 0 siblings : 32 @@ -656,7 +656,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5476.667 cache size : 1024 KB physical id : 0 siblings : 32 @@ -712,7 +712,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 3800.620 cache size : 1024 KB physical id : 0 siblings : 32 @@ -740,7 +740,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5270.714 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -768,7 +768,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 3841.209 cache size : 1024 KB physical id : 0 siblings : 32 @@ -796,7 +796,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5229.635 cache size : 1024 KB physical id : 0 siblings : 32 @@ -852,7 +852,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5221.417 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -908,7 +908,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5227.648 cache size : 1024 KB physical id : 0 siblings : 32 @@ -946,7 +946,7 @@ CPU family: 25 Model: 97 Model name: AMD Ryzen 9 7950X 16-Core Processor Stepping: 2 -CPU MHz: 400.000 +CPU MHz: 3226.111 CPU max MHz: 5881.0000 CPU min MHz: 400.0000 BogoMIPS: 8982.90 @@ -976,49 +976,49 @@ Flags: fpu vme de pse tsc msr pae mce cx8 apic se available: 1 nodes (0) node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 node 0 size: 128007 MB -node 0 free: 26449 MB +node 0 free: 10099 MB node distances: node 0 0: 10 ------------------------------------------------------------ 9. /proc/meminfo MemTotal: 131080068 kB -MemFree: 27084660 kB -MemAvailable: 127533888 kB -Buffers: 2618264 kB -Cached: 95786576 kB -SwapCached: 119020 kB -Active: 28196288 kB -Inactive: 70569692 kB -Active(anon): 359664 kB -Inactive(anon): 40528 kB -Active(file): 27836624 kB -Inactive(file): 70529164 kB +MemFree: 10338352 kB +MemAvailable: 57737092 kB +Buffers: 15372 kB +Cached: 47052800 kB +SwapCached: 67681200 kB +Active: 55891384 kB +Inactive: 60971372 kB +Active(anon): 30874416 kB +Inactive(anon): 38926248 kB +Active(file): 25016968 kB +Inactive(file): 22045124 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 683591672 kB -SwapFree: 683135880 kB +SwapFree: 503833560 kB Zswap: 0 kB Zswapped: 0 kB -Dirty: 84 kB -Writeback: 24 kB -AnonPages: 350444 kB -Mapped: 267784 kB -Shmem: 39052 kB -KReclaimable: 3330928 kB -Slab: 4054304 kB -SReclaimable: 3330928 kB -SUnreclaim: 723376 kB -KernelStack: 16352 kB -PageTables: 19788 kB +Dirty: 108 kB +Writeback: 0 kB +AnonPages: 69743812 kB +Mapped: 65292 kB +Shmem: 6016 kB +KReclaimable: 1584136 kB +Slab: 2096112 kB +SReclaimable: 1584136 kB +SUnreclaim: 511976 kB +KernelStack: 21408 kB +PageTables: 387184 kB SecPageTables: 0 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 749131704 kB -Committed_AS: 4986900 kB +Committed_AS: 190622584 kB VmallocTotal: 34359738367 kB -VmallocUsed: 252628 kB +VmallocUsed: 260108 kB VmallocChunk: 0 kB Percpu: 38400 kB HardwareCorrupted: 0 kB @@ -1034,9 +1034,9 @@ HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB Hugetlb: 0 kB -DirectMap4k: 20658592 kB -DirectMap2M: 109584384 kB -DirectMap1G: 4194304 kB +DirectMap4k: 36536736 kB +DirectMap2M: 95803392 kB +DirectMap1G: 2097152 kB ------------------------------------------------------------ 10. who -r ------------------------------------------------------------ @@ -1290,16 +1290,16 @@ dev.tty.ldisc_autoload = 1 dev.tty.legacy_tiocsti = 0 fs.aio-max-nr = 65536 fs.aio-nr = 0 -fs.dentry-state = 1332263 917667 45 0 225578 0 +fs.dentry-state = 165402 89865 45 0 8424 0 fs.dir-notify-enable = 1 fs.epoll.max_user_watches = 29163675 fs.fanotify.max_queued_events = 16384 fs.fanotify.max_user_groups = 128 fs.fanotify.max_user_marks = 1048576 fs.file-max = 9223372036854775807 -fs.file-nr = 5376 0 9223372036854775807 -fs.inode-nr = 1121004 15671 -fs.inode-state = 1121004 15671 0 0 0 0 0 +fs.file-nr = 6336 0 9223372036854775807 +fs.inode-nr = 229651 66261 +fs.inode-state = 229651 66261 0 0 0 0 0 fs.inotify.max_queued_events = 16384 fs.inotify.max_user_instances = 128 fs.inotify.max_user_watches = 65536 @@ -1327,7 +1327,7 @@ fs.quota.drops = 0 fs.quota.free_dquots = 0 fs.quota.lookups = 0 fs.quota.reads = 0 -fs.quota.syncs = 540 +fs.quota.syncs = 784 fs.quota.writes = 0 fs.suid_dumpable = 2 fs.verity.require_signatures = 0 @@ -1354,7 +1354,7 @@ kernel.ftrace_dump_on_oops = 0 kernel.ftrace_enabled = 1 kernel.hardlockup_all_cpu_backtrace = 0 kernel.hardlockup_panic = 0 -kernel.hostname = 2a6a3464ad42 +kernel.hostname = bec71595fc42 kernel.hotplug = kernel.hung_task_all_cpu_backtrace = 0 kernel.hung_task_check_count = 4194304 @@ -1386,7 +1386,7 @@ kernel.msgmnb = 16384 kernel.msgmni = 32000 kernel.ngroups_max = 65536 kernel.nmi_watchdog = 1 -kernel.ns_last_pid = 25458 +kernel.ns_last_pid = 25491 kernel.numa_balancing = 0 kernel.numa_balancing_promote_rate_limit_MBps = 65536 kernel.oops_all_cpu_backtrace = 0 @@ -1417,13 +1417,13 @@ kernel.printk_devkmsg = on kernel.printk_ratelimit = 5 kernel.printk_ratelimit_burst = 10 kernel.pty.max = 4096 -kernel.pty.nr = 10 +kernel.pty.nr = 19 kernel.pty.reserve = 1024 kernel.random.boot_id = d972d8ae-c9e1-46e1-875d-9f419475517a kernel.random.entropy_avail = 256 kernel.random.poolsize = 256 kernel.random.urandom_min_reseed_secs = 60 -kernel.random.uuid = bdef5c46-3ded-4aa8-8d1a-c5bc852c2738 +kernel.random.uuid = e49113aa-2004-4d35-aa1d-3380930623a0 kernel.random.write_wakeup_threshold = 256 kernel.randomize_va_space = 2 kernel.real-root-dev = 0 @@ -2243,7 +2243,7 @@ loop17 7:17 0 65.5M 1 loop loop18 7:18 0 10.8M 1 loop loop19 7:19 0 89.4M 1 loop loop20 7:20 0 91.7M 1 loop -loop22 7:22 0 89.4M 1 loop +loop21 7:21 0 89.4M 1 loop loop23 7:23 0 9.1M 1 loop loop24 7:24 0 150.6M 1 loop loop25 7:25 0 10.8M 1 loop diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/README.md b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/README.md index efe632bc7..66edea1e9 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/README.md +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/README.md @@ -1,5 +1,3 @@ -This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). - *Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* ## Host platform @@ -19,7 +17,7 @@ pip install -U cmind cm rm cache -f -cm pull repo mlcommons@mlperf-automations --checkout=a90475d2de72bf0622cebe8d5ca8eb8c9d872fbd +cm pull repo mlcommons@mlperf-automations --checkout=48ea6b46a7606d1c5d74909e94d5599dbe7ff9e1 cm run script \ --tags=app,mlperf,inference,generic,_nvidia,_resnet50,_tensorrt,_cuda,_valid,_r4.1-dev_default,_offline \ @@ -41,8 +39,8 @@ cm run script \ --env.CM_RUN_MLPERF_SUBMISSION_PREPROCESSOR=yes \ --env.CM_MLPERF_INFERENCE_PULL_CODE_CHANGES=yes \ --env.CM_MLPERF_INFERENCE_PULL_SRC_CHANGES=yes \ - --env.OUTPUT_BASE_DIR=/home/arjun/gh_action_results \ - --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/gh_action_submissions \ + --env.OUTPUT_BASE_DIR=/cm-mount/home/arjun/gh_action_results \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/cm-mount/home/arjun/gh_action_submissions \ --env.CM_MLPERF_SUBMITTER=MLCommons \ --env.CM_USE_DATASET_FROM_HOST=yes \ --env.CM_USE_MODEL_FROM_HOST=yes \ @@ -71,7 +69,7 @@ cm run script \ --env.CM_DOCKER_REUSE_EXISTING_CONTAINER=yes \ --env.CM_DOCKER_DETACHED_MODE=yes \ --env.CM_MLPERF_INFERENCE_RESULTS_DIR_=/home/arjun/gh_action_results/valid_results \ - --env.CM_DOCKER_CONTAINER_ID=2a6a3464ad42 \ + --env.CM_DOCKER_CONTAINER_ID=bec71595fc42 \ --env.CM_MLPERF_LOADGEN_COMPLIANCE_TEST=TEST04 \ --add_deps_recursive.compiler.tags=gcc \ --add_deps_recursive.coco2014-original.tags=_full \ @@ -104,11 +102,7 @@ cm run script \ --v=False \ --print_env=False \ --print_deps=False \ - --dump_version_info=True \ - --env.CM_DATASET_IMAGENET_PATH=/home/cmuser/CM/repos/local/cache/14a94e79cca24141/imagenet-2012-val \ - --env.OUTPUT_BASE_DIR=/cm-mount/home/arjun/gh_action_results \ - --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/cm-mount/home/arjun/gh_action_submissions \ - --env.MLPERF_SCRATCH_PATH=/home/cmuser/CM/repos/local/cache/a8c152aef5494496 + --dump_version_info=True ``` *Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), you should simply reload mlcommons@mlperf-automations without checkout and clean CM cache as follows:* @@ -130,4 +124,4 @@ Model Precision: int8 `acc`: `76.078`, Required accuracy for closed division `>= 75.6954` ### Performance Results -`Samples per second`: `44354.9` +`Samples per second`: `3633.97` diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/accuracy_console.out b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/accuracy_console.out index ae8ec4a15..b97e8878f 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/accuracy_console.out +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/accuracy_console.out @@ -1,7 +1,7 @@ -[2024-12-25 00:03:12,273 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 -[2024-12-25 00:03:12,540 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/Offline -[2024-12-25 00:03:12,540 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="AccuracyOnly" --gpu_res2res3_loop_count=1 --gpu_copy_streams=2 --gpu_inference_streams=1 --run_infer_on_copy_streams=false --use_deque_limit=true --gpu_batch_size=64 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5b88239b842b426eb109c73aa9379709.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/Offline/resnet50-Offline-gpu-b64-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Offline --model resnet50 -[2024-12-25 00:03:12,540 __init__.py:53 INFO] Overriding Environment +[2025-01-01 09:35:40,003 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 +[2025-01-01 09:35:40,281 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/Offline +[2025-01-01 09:35:40,281 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="AccuracyOnly" --gpu_res2res3_loop_count=1 --gpu_copy_streams=2 --gpu_inference_streams=1 --run_infer_on_copy_streams=false --use_deque_limit=true --gpu_batch_size=64 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/6f7792556bc04724b2408607970c13be.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/Offline/resnet50-Offline-gpu-b64-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Offline --model resnet50 +[2025-01-01 09:35:40,281 __init__.py:53 INFO] Overriding Environment benchmark : Benchmark.ResNet50 buffer_manager_thread_count : 0 data_dir : /home/cmuser/CM/repos/local/cache/a8c152aef5494496/data @@ -11,7 +11,7 @@ gpu_inference_streams : 1 gpu_res2res3_loop_count : 1 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2024.12.25-00.03.11 +log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2025.01.01-09.35.33 map_path : data_maps/imagenet/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf offline_expected_qps : 0.0 @@ -24,7 +24,7 @@ tensor_path : build/preprocessed_data/imagenet/ResNet50/int8_linear test_mode : AccuracyOnly use_deque_limit : True use_graphs : False -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5b88239b842b426eb109c73aa9379709.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/6f7792556bc04724b2408607970c13be.conf system_id : RTX4090x1 config_name : RTX4090x1_resnet50_Offline workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -38,7 +38,7 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5b88239b842b426eb109c73aa9379709.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/6f7792556bc04724b2408607970c13be.conf Creating QSL. Finished Creating QSL. Setting up SUT. @@ -58,7 +58,7 @@ Setting up SUT. [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.03118s. +Finished warmup. Ran for 5.03132s. Starting running actual test. No warnings encountered during test. @@ -72,8 +72,8 @@ Device Device:0.GPU processed: PerSampleCudaMemcpy Calls: 0 BatchedCudaMemcpy Calls: 782 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-25 00:03:24,552 run_harness.py:166 INFO] Result: Accuracy run detected. -[2024-12-25 00:03:24,552 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-imagenet.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/accuracy/mlperf_log_accuracy.json --imagenet-val-file data_maps/imagenet/val_map.txt --dtype int32 +[2025-01-01 09:36:22,582 run_harness.py:166 INFO] Result: Accuracy run detected. +[2025-01-01 09:36:22,583 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-imagenet.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/accuracy/mlperf_log_accuracy.json --imagenet-val-file data_maps/imagenet/val_map.txt --dtype int32 accuracy=76.078%, good=38039, total=50000 ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/cm-deps.mmd b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/cm-deps.mmd index 026242962..e63dc6dbe 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/cm-deps.mmd +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/cm-deps.mmd @@ -15,19 +15,19 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_package.numpy_) --> get,python3 get-cuda-devices,7a3ede4d3558427a_(_with-pycuda_) --> get,generic-python-lib,_package.numpy app-mlperf-inference,d775cac873ee4231_(_nvidia,_resnet50,_tensorrt,_cuda,_valid,_r4.1-dev_default,_offline_) --> get,cuda-devices,_with-pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,dataset,original,imagenet,_full - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,dataset,original,imagenet,_full + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> pull,git,repo generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,os detect-cpu,586c8a43320142f7 --> detect,os generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,cpu @@ -35,45 +35,45 @@ graph TD generate-mlperf-inference-user-conf,3af4475745964b93 --> get,mlcommons,inference,src get-mlperf-inference-sut-configs,c2fbf72009e2445b --> get,cache,dir,_name.mlperf-inference-sut-configs generate-mlperf-inference-user-conf,3af4475745964b93 --> get,sut,configs - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> generate,user-conf,mlperf,inference + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> generate,user-conf,mlperf,inference get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,dataset,original,imagenet,_full - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,dataset,original,imagenet,_full + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_cuda,_resnet50,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> get,generic-python-lib,_package.onnx - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_tensorrt,_cuda,_offline,_resnet50,_batch_size.64,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_cuda,_resnet50,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_resnet50,_tensorrt,_cuda,_offline,_batch_size.64,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> get,generic-python-lib,_package.onnx detect-cpu,586c8a43320142f7 --> detect,os benchmark-program,19f369ef47084895 --> detect,cpu benchmark-program-mlperf,cfff0132a8aa4018 --> benchmark-program,program - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/cm-deps.png b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/cm-deps.png index fc31976b6..abd274a47 100644 Binary files a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/cm-deps.png and b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/cm-deps.png differ diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/cm-version-info.json b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/cm-version-info.json index 599df0d49..3af783363 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/cm-version-info.json +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/cm-version-info.json @@ -167,7 +167,7 @@ "script_tags": "detect-os,detect,os,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090 )" } }, { @@ -187,7 +187,7 @@ "script_tags": "detect,cpu,detect-cpu,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090 )" } }, { @@ -197,7 +197,7 @@ "script_tags": "get,sys-utils-cm", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090 )" } }, { @@ -207,7 +207,7 @@ "script_tags": "get,mlperf,inference,nvidia,scratch,space", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090 )" } }, { @@ -227,7 +227,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "mlperf_logging", "version": "4.1.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090 )" } }, { @@ -237,7 +237,7 @@ "script_tags": "get,val,validation,dataset,imagenet,ILSVRC,image-classification,original", "script_variations": "full", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090 )" } }, { @@ -247,7 +247,7 @@ "script_tags": "get,raw,ml-model,resnet50,ml-model-resnet50,image-classification", "script_variations": "fp32,onnx,opset-8", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090 )" } }, { @@ -257,7 +257,7 @@ "script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons", "script_variations": "", "version": "master-git-2fdb814e6a765d994872fb99ee38f8c43418d5b0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090 )" } }, { @@ -267,7 +267,7 @@ "script_tags": "get,nvidia,mlperf,inference,common-code", "script_variations": "mlcommons", "version": "r4.0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090 )" } }, { @@ -287,7 +287,7 @@ "script_tags": "pull,git,repo,repository", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090 )" } }, { @@ -367,7 +367,7 @@ "script_tags": "generate,mlperf,inference,user-conf,inference-user-conf", "script_variations": "", "version": "", - "parent": 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run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090 )" } }, { @@ -777,7 +777,7 @@ "script_tags": "mlperf,benchmark-mlperf", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_cuda,_offline,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_resnet50,_tensorrt,_cuda,_offline,_rtx_4090 )" } } ] diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/os_info.json b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/os_info.json index 834f81f03..36b84384c 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/os_info.json +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/os_info.json @@ -26,5 +26,5 @@ ], "CM_HOST_PLATFORM_FLAVOR": "x86_64", "CM_HOST_PYTHON_BITS": "64", - "CM_HOST_SYSTEM_NAME": "2a6a3464ad42" + "CM_HOST_SYSTEM_NAME": "bec71595fc42" } \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/performance_console.out b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/performance_console.out index faebcd4f3..56d4dc47d 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/performance_console.out +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/performance_console.out @@ -1,7 +1,7 @@ -[2024-12-24 23:52:07,702 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 -[2024-12-24 23:52:07,962 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/Offline -[2024-12-24 23:52:07,962 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="PerformanceOnly" --gpu_res2res3_loop_count=1 --gpu_copy_streams=2 --gpu_inference_streams=1 --run_infer_on_copy_streams=false --use_deque_limit=true --gpu_batch_size=64 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/4ea07497db884eb584eeac67f07b2bef.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/Offline/resnet50-Offline-gpu-b64-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Offline --model resnet50 -[2024-12-24 23:52:07,962 __init__.py:53 INFO] Overriding Environment +[2025-01-01 07:23:48,851 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 +[2025-01-01 07:23:49,123 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/Offline +[2025-01-01 07:23:49,124 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="PerformanceOnly" --gpu_res2res3_loop_count=1 --gpu_copy_streams=2 --gpu_inference_streams=1 --run_infer_on_copy_streams=false --use_deque_limit=true --gpu_batch_size=64 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/cc59fc5fd1524411b5468954083dfed5.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/Offline/resnet50-Offline-gpu-b64-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Offline --model resnet50 +[2025-01-01 07:23:49,124 __init__.py:53 INFO] Overriding Environment benchmark : Benchmark.ResNet50 buffer_manager_thread_count : 0 data_dir : /home/cmuser/CM/repos/local/cache/a8c152aef5494496/data @@ -11,7 +11,7 @@ gpu_inference_streams : 1 gpu_res2res3_loop_count : 1 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2024.12.24-23.52.06 +log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2025.01.01-06.56.40 map_path : data_maps/imagenet/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf offline_expected_qps : 0.0 @@ -24,7 +24,7 @@ tensor_path : build/preprocessed_data/imagenet/ResNet50/int8_linear test_mode : PerformanceOnly use_deque_limit : True use_graphs : False -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/4ea07497db884eb584eeac67f07b2bef.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/cc59fc5fd1524411b5468954083dfed5.conf system_id : RTX4090x1 config_name : RTX4090x1_resnet50_Offline workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -38,7 +38,7 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/4ea07497db884eb584eeac67f07b2bef.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/cc59fc5fd1524411b5468954083dfed5.conf Creating QSL. Finished Creating QSL. Setting up SUT. @@ -58,7 +58,7 @@ Setting up SUT. [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.02978s. +Finished warmup. Ran for 5.03079s. Starting running actual test. ================================================ MLPerf Results Summary @@ -66,7 +66,7 @@ MLPerf Results Summary SUT name : LWIS_Server Scenario : Offline Mode : PerformanceOnly -Samples per second: 44354.9 +Samples per second: 3633.97 Result is : VALID Min duration satisfied : Yes Min queries satisfied : Yes @@ -75,15 +75,15 @@ Result is : VALID ================================================ Additional Stats ================================================ -Min latency (ns) : 185345230 -Max latency (ns) : 645627546417 -Mean latency (ns) : 322655572323 -50.00 percentile latency (ns) : 322603993114 -90.00 percentile latency (ns) : 581023033737 -95.00 percentile latency (ns) : 613325298535 -97.00 percentile latency (ns) : 626246842386 -99.00 percentile latency (ns) : 639168446304 -99.90 percentile latency (ns) : 644982685357 +Min latency (ns) : 212501451 +Max latency (ns) : 7880286936177 +Mean latency (ns) : 640135971137 +50.00 percentile latency (ns) : 5045376227510 +90.00 percentile latency (ns) : 7815701597962 +95.00 percentile latency (ns) : 7848065465747 +97.00 percentile latency (ns) : 7860943299479 +99.00 percentile latency (ns) : 7873842420964 +99.90 percentile latency (ns) : 7879643297455 ================================================ Test Parameters Used @@ -108,7 +108,7 @@ performance_issue_same : 0 performance_issue_same_index : 0 performance_sample_count : 1024 -No warnings encountered during test. +1 warning encountered. See detailed log. No errors encountered during test. Finished running actual test. @@ -118,7 +118,7 @@ Device Device:0.GPU processed: PerSampleCudaMemcpy Calls: 0 BatchedCudaMemcpy Calls: 447449 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-25 00:03:01,541 run_harness.py:166 INFO] Result: result_samples_per_second: 44354.9, Result is VALID +[2025-01-01 09:35:21,549 run_harness.py:166 INFO] Result: result_samples_per_second: 3633.97, Result is VALID ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/system_info.txt b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/system_info.txt index 3095eb4c4..c8f3efccc 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/system_info.txt +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/system_info.txt @@ -2,10 +2,10 @@ Platform Details ------------------------------------------------------------ 1. uname -a -Linux 2a6a3464ad42 6.8.0-51-generic #52-Ubuntu SMP PREEMPT_DYNAMIC Thu Dec 5 13:09:44 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux +Linux bec71595fc42 6.8.0-51-generic #52-Ubuntu SMP PREEMPT_DYNAMIC Thu Dec 5 13:09:44 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux ------------------------------------------------------------ 2. w - 00:03:03 up 6 days, 9:55, 0 users, load average: 1.00, 1.00, 1.01 + 09:35:24 up 13 days, 19:28, 0 users, load average: 8.74, 19.69, 28.50 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT ------------------------------------------------------------ 3. Username @@ -40,7 +40,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 4753.752 +cpu MHz : 5386.893 cache size : 1024 KB physical id : 0 siblings : 32 @@ -68,7 +68,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5419.996 +cpu MHz : 5396.848 cache size : 1024 KB physical id : 0 siblings : 32 @@ -96,7 +96,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5459.536 cache size : 1024 KB physical id : 0 siblings : 32 @@ -124,7 +124,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5192.384 cache size : 1024 KB physical id : 0 siblings : 32 @@ -152,7 +152,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5461.723 cache size : 1024 KB physical id : 0 siblings : 32 @@ -180,7 +180,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5463.467 cache size : 1024 KB physical id : 0 siblings : 32 @@ -208,7 +208,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4957.065 cache size : 1024 KB physical id : 0 siblings : 32 @@ -292,7 +292,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5204.928 cache size : 1024 KB physical id : 0 siblings : 32 @@ -320,7 +320,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4253.626 cache size : 1024 KB physical id : 0 siblings : 32 @@ -348,7 +348,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5239.767 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -404,7 +404,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 3506.855 +cpu MHz : 5263.494 cache size : 1024 KB physical id : 0 siblings : 32 @@ -432,7 +432,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 3476.715 cache size : 1024 KB physical id : 0 siblings : 32 @@ -460,7 +460,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 4298.874 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -516,7 +516,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5380.857 cache size : 1024 KB physical id : 0 siblings : 32 @@ -544,7 +544,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5450.968 cache size : 1024 KB physical id : 0 siblings : 32 @@ -628,7 +628,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 4765.247 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -656,7 +656,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 4247.876 +cpu MHz : 5379.315 cache size : 1024 KB physical id : 0 siblings : 32 @@ -684,7 +684,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4660.032 cache size : 1024 KB physical id : 0 siblings : 32 @@ -740,7 +740,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 3482.129 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -824,7 +824,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5195.019 cache size : 1024 KB physical id : 0 siblings : 32 @@ -852,7 +852,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5141.377 +cpu MHz : 5327.219 cache size : 1024 KB physical id : 0 siblings : 32 @@ -880,7 +880,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4908.013 cache size : 1024 KB physical id : 0 siblings : 32 @@ -908,7 +908,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5264.552 cache size : 1024 KB physical id : 0 siblings : 32 @@ -946,7 +946,7 @@ CPU family: 25 Model: 97 Model name: AMD Ryzen 9 7950X 16-Core Processor Stepping: 2 -CPU MHz: 400.000 +CPU MHz: 5386.893 CPU max MHz: 5881.0000 CPU min MHz: 400.0000 BogoMIPS: 8982.90 @@ -976,49 +976,49 @@ Flags: fpu vme de pse tsc msr pae mce cx8 apic se available: 1 nodes (0) node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 node 0 size: 128007 MB -node 0 free: 26383 MB +node 0 free: 4510 MB node distances: node 0 0: 10 ------------------------------------------------------------ 9. /proc/meminfo MemTotal: 131080068 kB -MemFree: 27016200 kB -MemAvailable: 127411576 kB -Buffers: 2615844 kB -Cached: 95736004 kB -SwapCached: 118936 kB -Active: 28190668 kB -Inactive: 70517720 kB -Active(anon): 354940 kB -Inactive(anon): 40532 kB -Active(file): 27835728 kB -Inactive(file): 70477188 kB +MemFree: 4617516 kB +MemAvailable: 61141648 kB +Buffers: 25260 kB +Cached: 57338976 kB +SwapCached: 16758280 kB +Active: 96513632 kB +Inactive: 25843660 kB +Active(anon): 58710880 kB +Inactive(anon): 6291144 kB +Active(file): 37802752 kB +Inactive(file): 19552516 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 683591672 kB -SwapFree: 683134856 kB +SwapFree: 549958132 kB Zswap: 0 kB Zswapped: 0 kB -Dirty: 40 kB +Dirty: 84 kB Writeback: 0 kB -AnonPages: 345448 kB -Mapped: 267664 kB -Shmem: 38932 kB -KReclaimable: 3329948 kB -Slab: 4054196 kB -SReclaimable: 3329948 kB -SUnreclaim: 724248 kB -KernelStack: 16192 kB -PageTables: 19320 kB +AnonPages: 64893896 kB +Mapped: 129836 kB +Shmem: 8952 kB +KReclaimable: 1425496 kB +Slab: 1942180 kB +SReclaimable: 1425496 kB +SUnreclaim: 516684 kB +KernelStack: 21552 kB +PageTables: 387332 kB SecPageTables: 0 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 749131704 kB -Committed_AS: 4981440 kB +Committed_AS: 190620176 kB VmallocTotal: 34359738367 kB -VmallocUsed: 252868 kB +VmallocUsed: 260412 kB VmallocChunk: 0 kB Percpu: 38400 kB HardwareCorrupted: 0 kB @@ -1034,9 +1034,9 @@ HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB Hugetlb: 0 kB -DirectMap4k: 20603296 kB -DirectMap2M: 109639680 kB -DirectMap1G: 4194304 kB +DirectMap4k: 36438432 kB +DirectMap2M: 95901696 kB +DirectMap1G: 2097152 kB ------------------------------------------------------------ 10. who -r ------------------------------------------------------------ @@ -1290,16 +1290,16 @@ dev.tty.ldisc_autoload = 1 dev.tty.legacy_tiocsti = 0 fs.aio-max-nr = 65536 fs.aio-nr = 0 -fs.dentry-state = 1327447 912860 45 0 220822 0 +fs.dentry-state = 214380 118744 45 0 8605 0 fs.dir-notify-enable = 1 fs.epoll.max_user_watches = 29163675 fs.fanotify.max_queued_events = 16384 fs.fanotify.max_user_groups = 128 fs.fanotify.max_user_marks = 1048576 fs.file-max = 9223372036854775807 -fs.file-nr = 5312 0 9223372036854775807 -fs.inode-nr = 1120945 15671 -fs.inode-state = 1120945 15671 0 0 0 0 0 +fs.file-nr = 6208 0 9223372036854775807 +fs.inode-nr = 270939 64136 +fs.inode-state = 270939 64136 0 0 0 0 0 fs.inotify.max_queued_events = 16384 fs.inotify.max_user_instances = 128 fs.inotify.max_user_watches = 65536 @@ -1327,7 +1327,7 @@ fs.quota.drops = 0 fs.quota.free_dquots = 0 fs.quota.lookups = 0 fs.quota.reads = 0 -fs.quota.syncs = 540 +fs.quota.syncs = 784 fs.quota.writes = 0 fs.suid_dumpable = 2 fs.verity.require_signatures = 0 @@ -1354,7 +1354,7 @@ kernel.ftrace_dump_on_oops = 0 kernel.ftrace_enabled = 1 kernel.hardlockup_all_cpu_backtrace = 0 kernel.hardlockup_panic = 0 -kernel.hostname = 2a6a3464ad42 +kernel.hostname = bec71595fc42 kernel.hotplug = kernel.hung_task_all_cpu_backtrace = 0 kernel.hung_task_check_count = 4194304 @@ -1386,7 +1386,7 @@ kernel.msgmnb = 16384 kernel.msgmni = 32000 kernel.ngroups_max = 65536 kernel.nmi_watchdog = 1 -kernel.ns_last_pid = 18592 +kernel.ns_last_pid = 18625 kernel.numa_balancing = 0 kernel.numa_balancing_promote_rate_limit_MBps = 65536 kernel.oops_all_cpu_backtrace = 0 @@ -1417,13 +1417,13 @@ kernel.printk_devkmsg = on kernel.printk_ratelimit = 5 kernel.printk_ratelimit_burst = 10 kernel.pty.max = 4096 -kernel.pty.nr = 10 +kernel.pty.nr = 19 kernel.pty.reserve = 1024 kernel.random.boot_id = d972d8ae-c9e1-46e1-875d-9f419475517a kernel.random.entropy_avail = 256 kernel.random.poolsize = 256 kernel.random.urandom_min_reseed_secs = 60 -kernel.random.uuid = be38938a-9f92-4991-bacc-f38cdd418843 +kernel.random.uuid = c7e69430-7a55-4c5f-943c-1489bc69196e kernel.random.write_wakeup_threshold = 256 kernel.randomize_va_space = 2 kernel.real-root-dev = 0 @@ -2243,7 +2243,7 @@ loop17 7:17 0 65.5M 1 loop loop18 7:18 0 10.8M 1 loop loop19 7:19 0 89.4M 1 loop loop20 7:20 0 91.7M 1 loop -loop22 7:22 0 89.4M 1 loop +loop21 7:21 0 89.4M 1 loop loop23 7:23 0 9.1M 1 loop loop24 7:24 0 150.6M 1 loop loop25 7:25 0 10.8M 1 loop diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/README.md b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/README.md index 9c573e71a..faff18b27 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/README.md +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/README.md @@ -1,5 +1,3 @@ -This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). - *Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* ## Host platform @@ -19,7 +17,7 @@ pip install -U cmind cm rm cache -f -cm pull repo mlcommons@mlperf-automations --checkout=a90475d2de72bf0622cebe8d5ca8eb8c9d872fbd +cm pull repo mlcommons@mlperf-automations --checkout=5faf15abe8521376226c9d408ed058bfca7ecdce cm run script \ --tags=app,mlperf,inference,generic,_nvidia,_resnet50,_tensorrt,_cuda,_valid,_r4.1-dev_default,_server \ @@ -41,8 +39,8 @@ cm run script \ --env.CM_RUN_MLPERF_SUBMISSION_PREPROCESSOR=yes \ --env.CM_MLPERF_INFERENCE_PULL_CODE_CHANGES=yes \ --env.CM_MLPERF_INFERENCE_PULL_SRC_CHANGES=yes \ - --env.OUTPUT_BASE_DIR=/home/arjun/gh_action_results \ - --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/gh_action_submissions \ + --env.OUTPUT_BASE_DIR=/cm-mount/home/arjun/gh_action_results \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/cm-mount/home/arjun/gh_action_submissions \ --env.CM_MLPERF_SUBMITTER=MLCommons \ --env.CM_USE_DATASET_FROM_HOST=yes \ --env.CM_USE_MODEL_FROM_HOST=yes \ @@ -71,7 +69,7 @@ cm run script \ --env.CM_DOCKER_REUSE_EXISTING_CONTAINER=yes \ --env.CM_DOCKER_DETACHED_MODE=yes \ --env.CM_MLPERF_INFERENCE_RESULTS_DIR_=/home/arjun/gh_action_results/valid_results \ - --env.CM_DOCKER_CONTAINER_ID=2a6a3464ad42 \ + --env.CM_DOCKER_CONTAINER_ID=bec71595fc42 \ --env.CM_MLPERF_LOADGEN_COMPLIANCE_TEST=TEST04 \ --add_deps_recursive.compiler.tags=gcc \ --add_deps_recursive.coco2014-original.tags=_full \ @@ -104,11 +102,7 @@ cm run script \ --v=False \ --print_env=False \ --print_deps=False \ - --dump_version_info=True \ - --env.CM_DATASET_IMAGENET_PATH=/home/cmuser/CM/repos/local/cache/14a94e79cca24141/imagenet-2012-val \ - --env.OUTPUT_BASE_DIR=/cm-mount/home/arjun/gh_action_results \ - --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/cm-mount/home/arjun/gh_action_submissions \ - --env.MLPERF_SCRATCH_PATH=/home/cmuser/CM/repos/local/cache/a8c152aef5494496 + --dump_version_info=True ``` *Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), you should simply reload mlcommons@mlperf-automations without checkout and clean CM cache as follows:* diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/accuracy_console.out b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/accuracy_console.out index de57e9a0d..0213e8c6f 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/accuracy_console.out +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/accuracy_console.out @@ -1,8 +1,8 @@ -[2024-12-25 01:10:08,213 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 -[2024-12-25 01:10:08,360 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/Server -[2024-12-25 01:10:08,360 harness.py:326 INFO] Updated LD_PRELOAD: /usr/lib/x86_64-linux-gnu/libjemalloc.so.2 -[2024-12-25 01:10:08,360 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="AccuracyOnly" --deque_timeout_usec=2000 --gpu_copy_streams=9 --gpu_inference_streams=2 --use_cuda_thread_per_device=true --use_deque_limit=true --gpu_batch_size=64 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/636ce016725f4cefac2a59e8463085bc.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/Server/resnet50-Server-gpu-b64-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Server --model resnet50 -[2024-12-25 01:10:08,360 __init__.py:53 INFO] Overriding Environment +[2025-01-01 10:25:49,333 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 +[2025-01-01 10:25:49,476 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/Server +[2025-01-01 10:25:49,476 harness.py:326 INFO] Updated LD_PRELOAD: /usr/lib/x86_64-linux-gnu/libjemalloc.so.2 +[2025-01-01 10:25:49,476 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="AccuracyOnly" --deque_timeout_usec=2000 --gpu_copy_streams=9 --gpu_inference_streams=2 --use_cuda_thread_per_device=true --use_deque_limit=true --gpu_batch_size=64 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/22e4e9ccc3684896a919f403f1ebba17.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/Server/resnet50-Server-gpu-b64-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Server --model resnet50 +[2025-01-01 10:25:49,476 __init__.py:53 INFO] Overriding Environment ERROR: ld.so: object '/usr/lib/x86_64-linux-gnu/libjemalloc.so.2' from LD_PRELOAD cannot be preloaded (cannot open shared object file): ignored. ERROR: ld.so: object '/usr/lib/x86_64-linux-gnu/libjemalloc.so.2' from LD_PRELOAD cannot be preloaded (cannot open shared object file): ignored. benchmark : Benchmark.ResNet50 @@ -14,7 +14,7 @@ gpu_copy_streams : 9 gpu_inference_streams : 2 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2024.12.25-01.10.07 +log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2025.01.01-10.25.48 map_path : data_maps/imagenet/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf precision : int8 @@ -28,7 +28,7 @@ test_mode : AccuracyOnly use_cuda_thread_per_device : True use_deque_limit : True use_graphs : True -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/636ce016725f4cefac2a59e8463085bc.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/22e4e9ccc3684896a919f403f1ebba17.conf system_id : RTX4090x1 config_name : RTX4090x1_resnet50_Server workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -42,7 +42,7 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/636ce016725f4cefac2a59e8463085bc.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/22e4e9ccc3684896a919f403f1ebba17.conf Creating QSL. Finished Creating QSL. Setting up SUT. @@ -94,7 +94,7 @@ Setting up SUT. [I] Creating cuda thread: 0 Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.14604s. +Finished warmup. Ran for 5.16883s. Starting running actual test. No warnings encountered during test. @@ -102,50 +102,54 @@ No warnings encountered during test. No errors encountered during test. Finished running actual test. Device Device:0.GPU processed: - 5 batches of size 1 - 1 batches of size 4 - 1 batches of size 5 - 3 batches of size 10 - 3 batches of size 13 - 3 batches of size 14 - 7 batches of size 18 - 1 batches of size 21 + 4 batches of size 1 + 1 batches of size 3 + 2 batches of size 5 + 1 batches of size 6 + 4 batches of size 10 + 5 batches of size 14 + 9 batches of size 18 + 2 batches of size 21 4 batches of size 22 - 1 batches of size 23 - 4 batches of size 24 - 1 batches of size 26 - 5 batches of size 27 - 2 batches of size 28 - 1 batches of size 29 - 3 batches of size 30 + 2 batches of size 24 + 6 batches of size 26 + 1 batches of size 27 + 3 batches of size 28 + 2 batches of size 29 + 1 batches of size 30 8 batches of size 32 - 4 batches of size 35 - 12 batches of size 40 - 2 batches of size 42 - 2 batches of size 44 - 2 batches of size 47 - 4 batches of size 49 - 8 batches of size 50 - 5 batches of size 51 - 9 batches of size 52 - 7 batches of size 53 + 3 batches of size 33 + 1 batches of size 34 + 1 batches of size 35 + 1 batches of size 36 + 1 batches of size 38 + 4 batches of size 41 + 1 batches of size 42 + 3 batches of size 44 + 6 batches of size 47 + 1 batches of size 48 + 1 batches of size 49 + 6 batches of size 50 + 1 batches of size 51 + 7 batches of size 52 + 20 batches of size 53 2 batches of size 54 - 15 batches of size 55 - 13 batches of size 56 - 10 batches of size 57 - 31 batches of size 58 - 15 batches of size 59 - 19 batches of size 60 - 30 batches of size 61 - 49 batches of size 62 - 25 batches of size 63 - 529 batches of size 64 + 12 batches of size 55 + 4 batches of size 56 + 8 batches of size 57 + 39 batches of size 58 + 22 batches of size 59 + 27 batches of size 60 + 25 batches of size 61 + 44 batches of size 62 + 27 batches of size 63 + 525 batches of size 64 Memcpy Calls: 0 - PerSampleCudaMemcpy Calls: 49995 - BatchedCudaMemcpy Calls: 5 + PerSampleCudaMemcpy Calls: 49996 + BatchedCudaMemcpy Calls: 4 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-25 01:10:22,557 run_harness.py:166 INFO] Result: Accuracy run detected. -[2024-12-25 01:10:22,557 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-imagenet.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/accuracy/mlperf_log_accuracy.json --imagenet-val-file data_maps/imagenet/val_map.txt --dtype int32 +[2025-01-01 10:26:27,438 run_harness.py:166 INFO] Result: Accuracy run detected. +[2025-01-01 10:26:27,438 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-imagenet.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/accuracy/mlperf_log_accuracy.json --imagenet-val-file data_maps/imagenet/val_map.txt --dtype int32 accuracy=76.078%, good=38039, total=50000 ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/cm-deps.mmd b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/cm-deps.mmd index c8fa39e66..2bffaf4b2 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/cm-deps.mmd +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/cm-deps.mmd @@ -15,19 +15,19 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_package.numpy_) --> get,python3 get-cuda-devices,7a3ede4d3558427a_(_with-pycuda_) --> get,generic-python-lib,_package.numpy app-mlperf-inference,d775cac873ee4231_(_nvidia,_resnet50,_tensorrt,_cuda,_valid,_r4.1-dev_default,_server_) --> get,cuda-devices,_with-pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,dataset,original,imagenet,_full - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,dataset,original,imagenet,_full + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> pull,git,repo generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,os detect-cpu,586c8a43320142f7 --> detect,os generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,cpu @@ -35,66 +35,66 @@ graph TD generate-mlperf-inference-user-conf,3af4475745964b93 --> get,mlcommons,inference,src get-mlperf-inference-sut-configs,c2fbf72009e2445b --> get,cache,dir,_name.mlperf-inference-sut-configs generate-mlperf-inference-user-conf,3af4475745964b93 --> get,sut,configs - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> generate,user-conf,mlperf,inference + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> generate,user-conf,mlperf,inference get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,dataset,original,imagenet,_full - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,dataset,original,imagenet,_full + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,dataset,original,imagenet,_full - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,dataset,original,imagenet,_full + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,nvidia,mitten get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_package.onnx - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_package.onnx - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_tensorrt,_server,_cuda,_resnet50,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_tensorrt,_cuda,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_cuda,_tensorrt,_resnet50,_server,_batch_size.64,_batch_size.32,_use-graphs,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_cuda,_tensorrt,_resnet50,_batch_size.32,_use-graphs,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> get,generic-python-lib,_package.onnx detect-cpu,586c8a43320142f7 --> detect,os benchmark-program,19f369ef47084895 --> detect,cpu benchmark-program-mlperf,cfff0132a8aa4018 --> benchmark-program,program - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/cm-deps.png b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/cm-deps.png index 0cc262940..3ce99ec4c 100644 Binary files a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/cm-deps.png and b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/cm-deps.png differ diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/cm-version-info.json b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/cm-version-info.json index a136aea63..7d0833143 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/cm-version-info.json +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/cm-version-info.json @@ -167,7 +167,7 @@ "script_tags": "detect-os,detect,os,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -187,7 +187,7 @@ "script_tags": "detect,cpu,detect-cpu,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -197,7 +197,7 @@ "script_tags": "get,sys-utils-cm", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -207,7 +207,7 @@ "script_tags": "get,mlperf,inference,nvidia,scratch,space", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -227,7 +227,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "mlperf_logging", "version": "4.1.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -237,7 +237,7 @@ "script_tags": "get,val,validation,dataset,imagenet,ILSVRC,image-classification,original", "script_variations": "full", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -247,7 +247,7 @@ "script_tags": "get,raw,ml-model,resnet50,ml-model-resnet50,image-classification", "script_variations": "fp32,onnx,opset-8", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -257,7 +257,7 @@ "script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons", "script_variations": "", "version": "master-git-2fdb814e6a765d994872fb99ee38f8c43418d5b0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -267,7 +267,7 @@ "script_tags": "get,nvidia,mlperf,inference,common-code", "script_variations": "mlcommons", "version": "r4.0", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -287,7 +287,7 @@ "script_tags": "pull,git,repo,repository", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -367,7 +367,7 @@ "script_tags": "generate,mlperf,inference,user-conf,inference-user-conf", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -387,7 +387,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.pycuda", "version": "2022.2.2", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -397,7 +397,7 @@ "script_tags": "get,nvidia,mitten,nvidia-mitten", "script_variations": "", "version": "master", - 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"parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -927,7 +927,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "onnx-graphsurgeon", "version": "0.3.27", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -947,7 +947,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.onnx", "version": "1.13.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } }, { @@ -987,7 +987,7 @@ "script_tags": "mlperf,benchmark-mlperf", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_tensorrt,_server,_cuda,_resnet50,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_resnet50,_server,_rtx_4090 )" } } ] diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/os_info.json b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/os_info.json index 834f81f03..36b84384c 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/os_info.json +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/os_info.json @@ -26,5 +26,5 @@ ], "CM_HOST_PLATFORM_FLAVOR": "x86_64", "CM_HOST_PYTHON_BITS": "64", - "CM_HOST_SYSTEM_NAME": "2a6a3464ad42" + "CM_HOST_SYSTEM_NAME": "bec71595fc42" } \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/performance_console.out b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/performance_console.out index 04d329064..ef726f227 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/performance_console.out +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/performance_console.out @@ -1,8 +1,8 @@ -[2024-12-25 00:59:35,056 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 -[2024-12-25 00:59:35,203 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/Server -[2024-12-25 00:59:35,203 harness.py:326 INFO] Updated LD_PRELOAD: /usr/lib/x86_64-linux-gnu/libjemalloc.so.2 -[2024-12-25 00:59:35,203 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="PerformanceOnly" --deque_timeout_usec=2000 --gpu_copy_streams=9 --gpu_inference_streams=2 --use_cuda_thread_per_device=true --use_deque_limit=true --gpu_batch_size=64 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/a201e989dd874417843577472ebd5492.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/Server/resnet50-Server-gpu-b64-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Server --model resnet50 -[2024-12-25 00:59:35,203 __init__.py:53 INFO] Overriding Environment +[2025-01-01 10:15:10,347 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 +[2025-01-01 10:15:10,488 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/Server +[2025-01-01 10:15:10,489 harness.py:326 INFO] Updated LD_PRELOAD: /usr/lib/x86_64-linux-gnu/libjemalloc.so.2 +[2025-01-01 10:15:10,489 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="PerformanceOnly" --deque_timeout_usec=2000 --gpu_copy_streams=9 --gpu_inference_streams=2 --use_cuda_thread_per_device=true --use_deque_limit=true --gpu_batch_size=64 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5a7d60a787a0401ea5a07d0441346c59.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/Server/resnet50-Server-gpu-b64-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario Server --model resnet50 +[2025-01-01 10:15:10,489 __init__.py:53 INFO] Overriding Environment ERROR: ld.so: object '/usr/lib/x86_64-linux-gnu/libjemalloc.so.2' from LD_PRELOAD cannot be preloaded (cannot open shared object file): ignored. ERROR: ld.so: object '/usr/lib/x86_64-linux-gnu/libjemalloc.so.2' from LD_PRELOAD cannot be preloaded (cannot open shared object file): ignored. benchmark : Benchmark.ResNet50 @@ -14,7 +14,7 @@ gpu_copy_streams : 9 gpu_inference_streams : 2 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2024.12.25-00.59.34 +log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2025.01.01-10.15.09 map_path : data_maps/imagenet/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf precision : int8 @@ -28,7 +28,7 @@ test_mode : PerformanceOnly use_cuda_thread_per_device : True use_deque_limit : True use_graphs : True -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/a201e989dd874417843577472ebd5492.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5a7d60a787a0401ea5a07d0441346c59.conf system_id : RTX4090x1 config_name : RTX4090x1_resnet50_Server workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -42,7 +42,7 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/a201e989dd874417843577472ebd5492.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5a7d60a787a0401ea5a07d0441346c59.conf Creating QSL. Finished Creating QSL. Setting up SUT. @@ -94,7 +94,7 @@ Setting up SUT. [I] Creating cuda thread: 0 Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.16186s. +Finished warmup. Ran for 5.15611s. Starting running actual test. ================================================ MLPerf Results Summary @@ -116,15 +116,15 @@ Additional Stats ================================================ Completed samples per second : 35357.75 -Min latency (ns) : 1721793 -Max latency (ns) : 239395333 -Mean latency (ns) : 3005541 -50.00 percentile latency (ns) : 2827351 -90.00 percentile latency (ns) : 3573039 -95.00 percentile latency (ns) : 3711462 -97.00 percentile latency (ns) : 3788290 -99.00 percentile latency (ns) : 3902820 -99.90 percentile latency (ns) : 75657243 +Min latency (ns) : 1719085 +Max latency (ns) : 110662823 +Mean latency (ns) : 2886657 +50.00 percentile latency (ns) : 2819887 +90.00 percentile latency (ns) : 3566001 +95.00 percentile latency (ns) : 3704432 +97.00 percentile latency (ns) : 3781485 +99.00 percentile latency (ns) : 3897364 +99.90 percentile latency (ns) : 22255064 ================================================ Test Parameters Used @@ -154,40 +154,45 @@ No warnings encountered during test. No errors encountered during test. Finished running actual test. Device Device:0.GPU processed: - 1 batches of size 34 + 2 batches of size 3 + 2 batches of size 10 + 1 batches of size 19 + 1 batches of size 24 + 3 batches of size 32 + 2 batches of size 34 2 batches of size 36 1 batches of size 38 1 batches of size 39 5 batches of size 40 - 9 batches of size 41 - 6 batches of size 42 - 20 batches of size 43 - 38 batches of size 44 - 43 batches of size 45 - 79 batches of size 46 - 129 batches of size 47 - 188 batches of size 48 - 267 batches of size 49 - 447 batches of size 50 - 527 batches of size 51 - 736 batches of size 52 - 1056 batches of size 53 - 1466 batches of size 54 - 1763 batches of size 55 - 2358 batches of size 56 - 2936 batches of size 57 - 3666 batches of size 58 - 4584 batches of size 59 - 5609 batches of size 60 - 6632 batches of size 61 - 7600 batches of size 62 - 8640 batches of size 63 - 286231 batches of size 64 + 16 batches of size 41 + 11 batches of size 42 + 23 batches of size 43 + 30 batches of size 44 + 51 batches of size 45 + 77 batches of size 46 + 127 batches of size 47 + 195 batches of size 48 + 291 batches of size 49 + 402 batches of size 50 + 525 batches of size 51 + 750 batches of size 52 + 1051 batches of size 53 + 1372 batches of size 54 + 1876 batches of size 55 + 2356 batches of size 56 + 2982 batches of size 57 + 3591 batches of size 58 + 4640 batches of size 59 + 5659 batches of size 60 + 6501 batches of size 61 + 7633 batches of size 62 + 8760 batches of size 63 + 286114 batches of size 64 Memcpy Calls: 0 PerSampleCudaMemcpy Calls: 21214751 BatchedCudaMemcpy Calls: 0 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-25 01:09:57,391 run_harness.py:166 INFO] Result: result_scheduled_samples_per_sec: 35357.9, Result is VALID +[2025-01-01 10:25:36,792 run_harness.py:166 INFO] Result: result_scheduled_samples_per_sec: 35357.9, Result is VALID ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/system_info.txt b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/system_info.txt index 4911c84bd..7d9655590 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/system_info.txt +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/system_info.txt @@ -2,10 +2,10 @@ Platform Details ------------------------------------------------------------ 1. uname -a -Linux 2a6a3464ad42 6.8.0-51-generic #52-Ubuntu SMP PREEMPT_DYNAMIC Thu Dec 5 13:09:44 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux +Linux bec71595fc42 6.8.0-51-generic #52-Ubuntu SMP PREEMPT_DYNAMIC Thu Dec 5 13:09:44 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux ------------------------------------------------------------ 2. w - 01:09:58 up 6 days, 11:02, 0 users, load average: 0.16, 0.25, 0.59 + 10:25:38 up 13 days, 20:18, 0 users, load average: 3.77, 3.87, 6.78 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT ------------------------------------------------------------ 3. Username @@ -40,7 +40,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5360.089 cache size : 1024 KB physical id : 0 siblings : 32 @@ -96,7 +96,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5310.237 cache size : 1024 KB physical id : 0 siblings : 32 @@ -264,7 +264,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4740.016 cache size : 1024 KB physical id : 0 siblings : 32 @@ -292,7 +292,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5189.538 cache size : 1024 KB physical id : 0 siblings : 32 @@ -320,7 +320,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5175.521 cache size : 1024 KB physical id : 0 siblings : 32 @@ -376,7 +376,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5208.643 +cpu MHz : 4481.474 cache size : 1024 KB physical id : 0 siblings : 32 @@ -404,7 +404,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5227.014 +cpu MHz : 5116.730 cache size : 1024 KB physical id : 0 siblings : 32 @@ -432,7 +432,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5115.225 cache size : 1024 KB physical id : 0 siblings : 32 @@ -460,7 +460,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 4237.462 +cpu MHz : 5177.399 cache size : 1024 KB physical id : 0 siblings : 32 @@ -544,7 +544,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5488.549 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -600,7 +600,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5389.631 cache size : 1024 KB physical id : 0 siblings : 32 @@ -740,7 +740,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4683.023 cache size : 1024 KB physical id : 0 siblings : 32 @@ -768,7 +768,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 4182.169 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -796,7 +796,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 4319.462 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -824,7 +824,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5129.978 cache size : 1024 KB physical id : 0 siblings : 32 @@ -852,7 +852,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5230.501 +cpu MHz : 3614.538 cache size : 1024 KB physical id : 0 siblings : 32 @@ -880,7 +880,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5125.086 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -908,7 +908,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4458.835 cache size : 1024 KB physical id : 0 siblings : 32 @@ -946,7 +946,7 @@ CPU family: 25 Model: 97 Model name: AMD Ryzen 9 7950X 16-Core Processor Stepping: 2 -CPU MHz: 400.000 +CPU MHz: 5360.089 CPU max MHz: 5881.0000 CPU min MHz: 400.0000 BogoMIPS: 8982.90 @@ -976,49 +976,49 @@ Flags: fpu vme de pse tsc msr pae mce cx8 apic se available: 1 nodes (0) node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 node 0 size: 128007 MB -node 0 free: 26425 MB +node 0 free: 9390 MB node distances: node 0 0: 10 ------------------------------------------------------------ 9. /proc/meminfo MemTotal: 131080068 kB -MemFree: 27059920 kB -MemAvailable: 127606512 kB -Buffers: 2620744 kB -Cached: 95880440 kB -SwapCached: 119112 kB -Active: 28199204 kB -Inactive: 70664936 kB -Active(anon): 361504 kB -Inactive(anon): 40524 kB -Active(file): 27837700 kB -Inactive(file): 70624412 kB +MemFree: 9615928 kB +MemAvailable: 23426716 kB +Buffers: 12984 kB +Cached: 13497828 kB +SwapCached: 104057480 kB +Active: 62094972 kB +Inactive: 55833788 kB +Active(anon): 61890484 kB +Inactive(anon): 42534704 kB +Active(file): 204488 kB +Inactive(file): 13299084 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 683591672 kB -SwapFree: 683135880 kB +SwapFree: 554857644 kB Zswap: 0 kB Zswapped: 0 kB -Dirty: 164 kB +Dirty: 36 kB Writeback: 0 kB -AnonPages: 352468 kB -Mapped: 269648 kB -Shmem: 39072 kB -KReclaimable: 3331968 kB -Slab: 4055292 kB -SReclaimable: 3331968 kB -SUnreclaim: 723324 kB -KernelStack: 16080 kB -PageTables: 19392 kB +AnonPages: 104414740 kB +Mapped: 86468 kB +Shmem: 7188 kB +KReclaimable: 1554704 kB +Slab: 2053836 kB +SReclaimable: 1554704 kB +SUnreclaim: 499132 kB +KernelStack: 20256 kB +PageTables: 281020 kB SecPageTables: 0 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 749131704 kB -Committed_AS: 4993008 kB +Committed_AS: 136517956 kB VmallocTotal: 34359738367 kB -VmallocUsed: 252724 kB +VmallocUsed: 259020 kB VmallocChunk: 0 kB Percpu: 38400 kB HardwareCorrupted: 0 kB @@ -1034,9 +1034,9 @@ HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB Hugetlb: 0 kB -DirectMap4k: 20689312 kB -DirectMap2M: 109553664 kB -DirectMap1G: 4194304 kB +DirectMap4k: 36790688 kB +DirectMap2M: 95549440 kB +DirectMap1G: 2097152 kB ------------------------------------------------------------ 10. who -r ------------------------------------------------------------ @@ -1290,16 +1290,16 @@ dev.tty.ldisc_autoload = 1 dev.tty.legacy_tiocsti = 0 fs.aio-max-nr = 65536 fs.aio-nr = 0 -fs.dentry-state = 1337447 922821 45 0 230616 0 +fs.dentry-state = 112379 63660 45 0 6854 0 fs.dir-notify-enable = 1 fs.epoll.max_user_watches = 29163675 fs.fanotify.max_queued_events = 16384 fs.fanotify.max_user_groups = 128 fs.fanotify.max_user_marks = 1048576 fs.file-max = 9223372036854775807 -fs.file-nr = 5376 0 9223372036854775807 -fs.inode-nr = 1121150 15671 -fs.inode-state = 1121150 15671 0 0 0 0 0 +fs.file-nr = 6080 0 9223372036854775807 +fs.inode-nr = 148438 36226 +fs.inode-state = 148438 36226 0 0 0 0 0 fs.inotify.max_queued_events = 16384 fs.inotify.max_user_instances = 128 fs.inotify.max_user_watches = 65536 @@ -1327,7 +1327,7 @@ fs.quota.drops = 0 fs.quota.free_dquots = 0 fs.quota.lookups = 0 fs.quota.reads = 0 -fs.quota.syncs = 540 +fs.quota.syncs = 784 fs.quota.writes = 0 fs.suid_dumpable = 2 fs.verity.require_signatures = 0 @@ -1354,7 +1354,7 @@ kernel.ftrace_dump_on_oops = 0 kernel.ftrace_enabled = 1 kernel.hardlockup_all_cpu_backtrace = 0 kernel.hardlockup_panic = 0 -kernel.hostname = 2a6a3464ad42 +kernel.hostname = bec71595fc42 kernel.hotplug = kernel.hung_task_all_cpu_backtrace = 0 kernel.hung_task_check_count = 4194304 @@ -1386,7 +1386,7 @@ kernel.msgmnb = 16384 kernel.msgmni = 32000 kernel.ngroups_max = 65536 kernel.nmi_watchdog = 1 -kernel.ns_last_pid = 32862 +kernel.ns_last_pid = 32901 kernel.numa_balancing = 0 kernel.numa_balancing_promote_rate_limit_MBps = 65536 kernel.oops_all_cpu_backtrace = 0 @@ -1417,13 +1417,13 @@ kernel.printk_devkmsg = on kernel.printk_ratelimit = 5 kernel.printk_ratelimit_burst = 10 kernel.pty.max = 4096 -kernel.pty.nr = 10 +kernel.pty.nr = 19 kernel.pty.reserve = 1024 kernel.random.boot_id = d972d8ae-c9e1-46e1-875d-9f419475517a kernel.random.entropy_avail = 256 kernel.random.poolsize = 256 kernel.random.urandom_min_reseed_secs = 60 -kernel.random.uuid = f0eb46f1-cc0c-4e6d-a871-431c15f31905 +kernel.random.uuid = 89d9e662-7bff-4f24-adb0-43a515ec810c kernel.random.write_wakeup_threshold = 256 kernel.randomize_va_space = 2 kernel.real-root-dev = 0 @@ -2243,7 +2243,7 @@ loop17 7:17 0 65.5M 1 loop loop18 7:18 0 10.8M 1 loop loop19 7:19 0 89.4M 1 loop loop20 7:20 0 91.7M 1 loop -loop22 7:22 0 89.4M 1 loop +loop21 7:21 0 89.4M 1 loop loop23 7:23 0 9.1M 1 loop loop24 7:24 0 150.6M 1 loop loop25 7:25 0 10.8M 1 loop diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/README.md b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/README.md index 212847c59..3456f8331 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/README.md +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/README.md @@ -1,5 +1,3 @@ -This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). - *Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* ## Host platform @@ -19,7 +17,7 @@ pip install -U cmind cm rm cache -f -cm pull repo mlcommons@mlperf-automations --checkout=a90475d2de72bf0622cebe8d5ca8eb8c9d872fbd +cm pull repo mlcommons@mlperf-automations --checkout=48ea6b46a7606d1c5d74909e94d5599dbe7ff9e1 cm run script \ --tags=app,mlperf,inference,generic,_nvidia,_resnet50,_tensorrt,_cuda,_valid,_r4.1-dev_default,_singlestream \ @@ -41,8 +39,8 @@ cm run script \ --env.CM_RUN_MLPERF_SUBMISSION_PREPROCESSOR=yes \ --env.CM_MLPERF_INFERENCE_PULL_CODE_CHANGES=yes \ --env.CM_MLPERF_INFERENCE_PULL_SRC_CHANGES=yes \ - --env.OUTPUT_BASE_DIR=/home/arjun/gh_action_results \ - --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/gh_action_submissions \ + --env.OUTPUT_BASE_DIR=/cm-mount/home/arjun/gh_action_results \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/cm-mount/home/arjun/gh_action_submissions \ --env.CM_MLPERF_SUBMITTER=MLCommons \ --env.CM_USE_DATASET_FROM_HOST=yes \ --env.CM_USE_MODEL_FROM_HOST=yes \ @@ -101,11 +99,7 @@ cm run script \ --v=False \ --print_env=False \ --print_deps=False \ - --dump_version_info=True \ - --env.CM_DATASET_IMAGENET_PATH=/home/cmuser/CM/repos/local/cache/14a94e79cca24141/imagenet-2012-val \ - --env.OUTPUT_BASE_DIR=/cm-mount/home/arjun/gh_action_results \ - --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/cm-mount/home/arjun/gh_action_submissions \ - --env.MLPERF_SCRATCH_PATH=/home/cmuser/CM/repos/local/cache/a8c152aef5494496 + --dump_version_info=True ``` *Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), you should simply reload mlcommons@mlperf-automations without checkout and clean CM cache as follows:* @@ -127,4 +121,4 @@ Model Precision: int8 `acc`: `76.064`, Required accuracy for closed division `>= 75.6954` ### Performance Results -`90th percentile latency (ns)`: `282518.0` +`90th percentile latency (ns)`: `300962.0` diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/accuracy_console.out b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/accuracy_console.out index 44f5ab840..11e819dca 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/accuracy_console.out +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/accuracy_console.out @@ -1,7 +1,7 @@ -[2024-12-24 23:29:38,531 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 -[2024-12-24 23:29:38,694 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/SingleStream -[2024-12-24 23:29:38,694 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="AccuracyOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=1 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5e30f9947535454b8bb78b989ee362b4.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/SingleStream/resnet50-SingleStream-gpu-b1-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario SingleStream --model resnet50 -[2024-12-24 23:29:38,694 __init__.py:53 INFO] Overriding Environment +[2025-01-01 04:58:03,552 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 +[2025-01-01 04:58:03,714 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/SingleStream +[2025-01-01 04:58:03,714 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="AccuracyOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=1 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/9d7e88fdc93f42a1b5b406f2f2ad6548.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/SingleStream/resnet50-SingleStream-gpu-b1-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario SingleStream --model resnet50 +[2025-01-01 04:58:03,714 __init__.py:53 INFO] Overriding Environment benchmark : Benchmark.ResNet50 buffer_manager_thread_count : 0 data_dir : /home/cmuser/CM/repos/local/cache/a8c152aef5494496/data @@ -11,7 +11,7 @@ gpu_copy_streams : 1 gpu_inference_streams : 1 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2024.12.24-23.29.37 +log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2025.01.01-04.53.50 map_path : data_maps/imagenet/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf precision : int8 @@ -23,7 +23,7 @@ tensor_path : build/preprocessed_data/imagenet/ResNet50/int8_linear test_mode : AccuracyOnly use_deque_limit : True use_graphs : True -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5e30f9947535454b8bb78b989ee362b4.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/9d7e88fdc93f42a1b5b406f2f2ad6548.conf system_id : RTX4090x1 config_name : RTX4090x1_resnet50_SingleStream workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -37,7 +37,7 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5e30f9947535454b8bb78b989ee362b4.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/9d7e88fdc93f42a1b5b406f2f2ad6548.conf Creating QSL. Finished Creating QSL. Setting up SUT. @@ -56,7 +56,7 @@ Setting up SUT. [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.01467s. +Finished warmup. Ran for 5.01463s. Starting running actual test. No warnings encountered during test. @@ -69,8 +69,8 @@ Device Device:0.GPU processed: PerSampleCudaMemcpy Calls: 0 BatchedCudaMemcpy Calls: 50000 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-24 23:30:25,785 run_harness.py:166 INFO] Result: Accuracy run detected. -[2024-12-24 23:30:25,785 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-imagenet.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/accuracy/mlperf_log_accuracy.json --imagenet-val-file data_maps/imagenet/val_map.txt --dtype int32 +[2025-01-01 05:20:48,257 run_harness.py:166 INFO] Result: Accuracy run detected. +[2025-01-01 05:20:48,260 __init__.py:46 INFO] Running command: python3 /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/vision/classification_and_detection/tools/accuracy-imagenet.py --mlperf-accuracy-file /cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/accuracy/mlperf_log_accuracy.json --imagenet-val-file data_maps/imagenet/val_map.txt --dtype int32 accuracy=76.064%, good=38032, total=50000 ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/cm-deps.mmd b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/cm-deps.mmd index 55021f305..82f9848b6 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/cm-deps.mmd +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/cm-deps.mmd @@ -9,8 +9,8 @@ graph TD app-mlperf-inference,d775cac873ee4231_(_nvidia,_resnet50,_tensorrt,_cuda,_valid,_r4.1-dev_default,_singlestream_) --> get,mlperf,inference,utils download-file,9cdc8dc41aae437e_(_wget,_url.http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz_) --> detect,os download-and-extract,c67e81a4ce2649f5_(_extract,_wget,_url.http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz_) --> download,file,_wget,_url.http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz - extract-file,3f0b76219d004817_(_path./home/cmuser/CM/repos/local/cache/2d1d131cf5544f42/caffe_ilsvrc12.tar.gz_) --> detect,os - download-and-extract,c67e81a4ce2649f5_(_extract,_wget,_url.http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz_) --> extract,file,_path./home/cmuser/CM/repos/local/cache/2d1d131cf5544f42/caffe_ilsvrc12.tar.gz + extract-file,3f0b76219d004817_(_path./home/cmuser/CM/repos/local/cache/ffc5f5e44d0745c6/caffe_ilsvrc12.tar.gz_) --> detect,os + download-and-extract,c67e81a4ce2649f5_(_extract,_wget,_url.http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz_) --> extract,file,_path./home/cmuser/CM/repos/local/cache/ffc5f5e44d0745c6/caffe_ilsvrc12.tar.gz get-dataset-imagenet-aux,bb2c6dd8c8c64217 --> download-and-extract,_extract,_wget,_url.http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz app-mlperf-inference,d775cac873ee4231_(_nvidia,_resnet50,_tensorrt,_cuda,_valid,_r4.1-dev_default,_singlestream_) --> get,dataset-aux,imagenet-aux get-cuda,46d133d9ef92422d_(_toolkit_) --> detect,os @@ -26,22 +26,22 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_package.numpy_) --> get,generic-python-lib,_pip get-cuda-devices,7a3ede4d3558427a_(_with-pycuda_) --> get,generic-python-lib,_package.numpy app-mlperf-inference,d775cac873ee4231_(_nvidia,_resnet50,_tensorrt,_cuda,_valid,_r4.1-dev_default,_singlestream_) --> get,cuda-devices,_with-pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,mlperf,inference,nvidia,scratch,space get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,dataset,original,imagenet,_full + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,dataset,original,imagenet,_full download-file,9cdc8dc41aae437e_(_cmutil,_url.https://zenodo.org/record/2592612/files/resnet50_v1.onnx_) --> detect,os download-and-extract,c67e81a4ce2649f5_(_url.https://zenodo.org/record/2592612/files/resnet50_v1.onnx_) --> download,file,_cmutil,_url.https://zenodo.org/record/2592612/files/resnet50_v1.onnx get-ml-model-resnet50,56203e4e998b4bc0_(_fp32,_onnx,_opset-8_) --> download-and-extract,_url.https://zenodo.org/record/2592612/files/resnet50_v1.onnx - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> pull,git,repo generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,os detect-cpu,586c8a43320142f7 --> detect,os generate-mlperf-inference-user-conf,3af4475745964b93 --> detect,cpu @@ -49,9 +49,9 @@ graph TD generate-mlperf-inference-user-conf,3af4475745964b93 --> get,mlcommons,inference,src get-mlperf-inference-sut-configs,c2fbf72009e2445b --> get,cache,dir,_name.mlperf-inference-sut-configs generate-mlperf-inference-user-conf,3af4475745964b93 --> get,sut,configs - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> generate,user-conf,mlperf,inference + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> generate,user-conf,mlperf,inference get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,generic-python-lib,_package.pycuda get-nvidia-mitten,1c045f2902374de9 --> detect,os get-nvidia-mitten,1c045f2902374de9 --> get,python3 get-generic-python-lib,94b62a682bc44791_(_pycuda_) --> detect,os @@ -64,9 +64,9 @@ graph TD get-nvidia-mitten,1c045f2902374de9 --> get,generic-python-lib,_pycuda get-git-repo,ed603e7292974f10_(_repo.https://github.com/NVIDIA/mitten_) --> detect,os get-nvidia-mitten,1c045f2902374de9 --> get,git,_repo.https://github.com/NVIDIA/mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,tensorrt build-mlperf-inference-server-nvidia,f37403af5e9f4541_(_mlcommons_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os build-mlperf-inference-server-nvidia,f37403af5e9f4541_(_mlcommons_) --> detect,cpu @@ -124,60 +124,60 @@ graph TD get-generic-python-lib,94b62a682bc44791_(_pycuda_) --> get,python3 add-custom-nvidia-system,b2e6c46c6e8745a3_(_mlcommons_) --> get,generic-python-lib,_pycuda build-mlperf-inference-server-nvidia,f37403af5e9f4541_(_mlcommons_) --> add,custom,system,nvidia,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,dataset,original,imagenet,_full - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,dataset,original,imagenet,_full + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,nvidia,mitten - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,cuda,_cudnn - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,tensorrt - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> detect,os + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,cuda,_cudnn + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,tensorrt + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> build,nvidia,inference,server,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> detect,os detect-cpu,586c8a43320142f7 --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> detect,cpu - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> get,sys-utils-cm - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> detect,cpu + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> get,sys-utils-cm + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> get,mlperf,inference,nvidia,scratch,space,_version.4_0 get-generic-python-lib,94b62a682bc44791_(_mlperf_logging_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> get,dataset,original,imagenet,_full - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> get,mlcommons,inference,src - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> get,generic-python-lib,_mlperf_logging + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> get,dataset,original,imagenet,_full + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> get,ml-model,resnet50,_fp32,_onnx,_opset-8 + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> get,mlcommons,inference,src + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> get,nvidia,mlperf,inference,common-code,_mlcommons pull-git-repo,c23132ed65c4421d --> detect,os - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> pull,git,repo + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> pull,git,repo get-generic-python-lib,94b62a682bc44791_(_package.pycuda_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> get,nvidia,mitten + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> get,generic-python-lib,_package.pycuda + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> get,nvidia,mitten get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> get,generic-python-lib,_package.onnx - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_package.onnx - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev_) --> save,mlperf,inference,state - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev_) --> save,mlperf,inference,state + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev get-generic-python-lib,94b62a682bc44791_(_onnx-graphsurgeon_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,generic-python-lib,_onnx-graphsurgeon get-generic-python-lib,94b62a682bc44791_(_package.onnx_) --> get,python3 - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> get,generic-python-lib,_package.onnx + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> get,generic-python-lib,_package.onnx detect-cpu,586c8a43320142f7 --> detect,os benchmark-program,19f369ef47084895 --> detect,cpu benchmark-program-mlperf,cfff0132a8aa4018 --> benchmark-program,program - app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file + app-mlperf-inference-nvidia,bc3b17fb430f4732_(_run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090_) --> benchmark-mlperf \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/cm-deps.png b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/cm-deps.png index 2e77e0bae..eef02c067 100644 Binary files a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/cm-deps.png and b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/cm-deps.png differ diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/cm-version-info.json b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/cm-version-info.json index a80d7e7d7..1463ef72b 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/cm-version-info.json +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/cm-version-info.json @@ -107,15 +107,15 @@ "script_tags": "detect-os,detect,os,info", "script_variations": "", "version": "", - "parent": "extract-file,3f0b76219d004817 ( path./home/cmuser/CM/repos/local/cache/2d1d131cf5544f42/caffe_ilsvrc12.tar.gz )" + "parent": "extract-file,3f0b76219d004817 ( path./home/cmuser/CM/repos/local/cache/ffc5f5e44d0745c6/caffe_ilsvrc12.tar.gz )" } }, { - "extract,file,_path./home/cmuser/CM/repos/local/cache/2d1d131cf5544f42/caffe_ilsvrc12.tar.gz": { + "extract,file,_path./home/cmuser/CM/repos/local/cache/ffc5f5e44d0745c6/caffe_ilsvrc12.tar.gz": { "script_uid": "3f0b76219d004817", "script_alias": "extract-file", "script_tags": "extract,file", - "script_variations": "path./home/cmuser/CM/repos/local/cache/2d1d131cf5544f42/caffe_ilsvrc12.tar.gz", + "script_variations": "path./home/cmuser/CM/repos/local/cache/ffc5f5e44d0745c6/caffe_ilsvrc12.tar.gz", "version": "", "parent": "download-and-extract,c67e81a4ce2649f5 ( extract,_wget,_url.http://dl.caffe.berkeleyvision.org/caffe_ilsvrc12.tar.gz )" } @@ -277,7 +277,7 @@ "script_tags": "detect-os,detect,os,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090 )" } }, { @@ -297,7 +297,7 @@ "script_tags": "detect,cpu,detect-cpu,info", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090 )" } }, { @@ -307,7 +307,7 @@ "script_tags": "get,sys-utils-cm", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090 )" } }, { @@ -317,7 +317,7 @@ "script_tags": "get,mlperf,inference,nvidia,scratch,space", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090 )" } }, { @@ -337,7 +337,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "mlperf_logging", "version": "4.1.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090 )" } }, { @@ -347,7 +347,7 @@ "script_tags": "get,val,validation,dataset,imagenet,ILSVRC,image-classification,original", "script_variations": "full", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090 )" } }, { @@ -387,7 +387,7 @@ "script_tags": "get,raw,ml-model,resnet50,ml-model-resnet50,image-classification", "script_variations": "fp32,onnx,opset-8", "version": "", - "parent": 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"app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev )" } }, { - "reproduce,mlperf,inference,nvidia,harness,_build_engine,_singlestream,_resnet50,_tensorrt,_cuda,_batch_size.1,_v4.1-dev": { + "reproduce,mlperf,inference,nvidia,harness,_build_engine,_cuda,_tensorrt,_singlestream,_resnet50,_batch_size.1,_v4.1-dev": { "script_uid": "bc3b17fb430f4732", "script_alias": "app-mlperf-inference-nvidia", "script_tags": "reproduce,mlcommons,mlperf,inference,harness,nvidia-harness,nvidia", - "script_variations": "build_engine,singlestream,resnet50,tensorrt,cuda,batch_size.1,v4.1-dev", + "script_variations": "build_engine,cuda,tensorrt,singlestream,resnet50,batch_size.1,v4.1-dev", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090 )" } }, { - "reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_resnet50,_tensorrt,_cuda,_v4.1-dev": { + "reproduce,mlperf,inference,nvidia,harness,_preprocess_data,_cuda,_tensorrt,_resnet50,_v4.1-dev": { "script_uid": "bc3b17fb430f4732", "script_alias": "app-mlperf-inference-nvidia", "script_tags": "reproduce,mlcommons,mlperf,inference,harness,nvidia-harness,nvidia", - "script_variations": "preprocess_data,resnet50,tensorrt,cuda,v4.1-dev", + "script_variations": "preprocess_data,cuda,tensorrt,resnet50,v4.1-dev", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090 )" } }, { @@ -1757,7 +1757,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "onnx-graphsurgeon", "version": "0.3.27", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090 )" } }, { @@ -1777,7 +1777,7 @@ "script_tags": "get,install,generic,pip-package,generic-python-lib", "script_variations": "package.onnx", "version": "1.13.1", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090 )" } }, { @@ -1817,7 +1817,7 @@ "script_tags": "mlperf,benchmark-mlperf", "script_variations": "", "version": "", - "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_singlestream,_resnet50,_tensorrt,_cuda,_rtx_4090 )" + "parent": "app-mlperf-inference-nvidia,bc3b17fb430f4732 ( run_harness,_cuda,_tensorrt,_singlestream,_resnet50,_rtx_4090 )" } } ] diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/os_info.json b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/os_info.json index 834f81f03..36b84384c 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/os_info.json +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/os_info.json @@ -26,5 +26,5 @@ ], "CM_HOST_PLATFORM_FLAVOR": "x86_64", "CM_HOST_PYTHON_BITS": "64", - "CM_HOST_SYSTEM_NAME": "2a6a3464ad42" + "CM_HOST_SYSTEM_NAME": "bec71595fc42" } \ No newline at end of file diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/performance_console.out b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/performance_console.out index 2259a62f3..ef7facdc7 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/performance_console.out +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/performance_console.out @@ -1,7 +1,7 @@ -[2024-12-24 23:18:52,043 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 -[2024-12-24 23:18:52,216 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/SingleStream -[2024-12-24 23:18:52,216 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="PerformanceOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=1 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/bbff821fae28443ba2c388903a66b395.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/SingleStream/resnet50-SingleStream-gpu-b1-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario SingleStream --model resnet50 -[2024-12-24 23:18:52,216 __init__.py:53 INFO] Overriding Environment +[2025-01-01 03:44:53,760 main.py:229 INFO] Detected system ID: KnownSystem.RTX4090x1 +[2025-01-01 03:44:53,936 generate_conf_files.py:107 INFO] Generated measurements/ entries for RTX4090x1_TRT/resnet50/SingleStream +[2025-01-01 03:44:53,936 __init__.py:46 INFO] Running command: ./build/bin/harness_default --logfile_outdir="/cm-mount/home/arjun/gh_action_results/valid_results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/performance/run_1" --logfile_prefix="mlperf_log_" --performance_sample_count=2048 --test_mode="PerformanceOnly" --gpu_copy_streams=1 --gpu_inference_streams=1 --use_deque_limit=true --gpu_batch_size=1 --map_path="data_maps/imagenet/val_map.txt" --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf" --tensor_path="build/preprocessed_data/imagenet/ResNet50/int8_linear" --use_graphs=true --user_conf_path="/home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/ab704eca02a94a9ab3d3af2432867d94.conf" --gpu_engines="./build/engines/RTX4090x1/resnet50/SingleStream/resnet50-SingleStream-gpu-b1-int8.lwis_k_99_MaxP.plan" --max_dlas=0 --scenario SingleStream --model resnet50 +[2025-01-01 03:44:53,936 __init__.py:53 INFO] Overriding Environment benchmark : Benchmark.ResNet50 buffer_manager_thread_count : 0 data_dir : /home/cmuser/CM/repos/local/cache/a8c152aef5494496/data @@ -11,7 +11,7 @@ gpu_copy_streams : 1 gpu_inference_streams : 1 input_dtype : int8 input_format : linear -log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2024.12.24-23.18.51 +log_dir : /home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/logs/2025.01.01-03.31.49 map_path : data_maps/imagenet/val_map.txt mlperf_conf_path : /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf precision : int8 @@ -23,7 +23,7 @@ tensor_path : build/preprocessed_data/imagenet/ResNet50/int8_linear test_mode : PerformanceOnly use_deque_limit : True use_graphs : True -user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/bbff821fae28443ba2c388903a66b395.conf +user_conf_path : /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/ab704eca02a94a9ab3d3af2432867d94.conf system_id : RTX4090x1 config_name : RTX4090x1_resnet50_SingleStream workload_setting : WorkloadSetting(HarnessType.LWIS, AccuracyTarget.k_99, PowerSetting.MaxP) @@ -37,7 +37,7 @@ power_limit : None cpu_freq : None &&&& RUNNING Default_Harness # ./build/bin/harness_default [I] mlperf.conf path: /home/cmuser/CM/repos/local/cache/90c7069b92e34687/inference/mlperf.conf -[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/bbff821fae28443ba2c388903a66b395.conf +[I] user.conf path: /home/cmuser/CM/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/ab704eca02a94a9ab3d3af2432867d94.conf Creating QSL. Finished Creating QSL. Setting up SUT. @@ -56,7 +56,7 @@ Setting up SUT. [I] Creating batcher thread: 0 EnableBatcherThreadPerDevice: false Finished setting up SUT. Starting warmup. Running for a minimum of 5 seconds. -Finished warmup. Ran for 5.01481s. +Finished warmup. Ran for 5.10013s. Starting running actual test. ================================================ MLPerf Results Summary @@ -64,32 +64,32 @@ MLPerf Results Summary SUT name : LWIS_Server Scenario : SingleStream Mode : PerformanceOnly -90th percentile latency (ns) : 282507 +90th percentile latency (ns) : 300822 Result is : VALID Min duration satisfied : Yes Min queries satisfied : Yes Early stopping satisfied: Yes Early Stopping Result: - * Processed at least 64 queries (2130236). - * Would discard 212004 highest latency queries. - * Early stopping 90th percentile estimate: 282518 - * Early stopping 99th percentile estimate: 288269 + * Processed at least 64 queries (151886). + * Would discard 14915 highest latency queries. + * Early stopping 90th percentile estimate: 300962 + * Early stopping 99th percentile estimate: 1789992 ================================================ Additional Stats ================================================ -QPS w/ loadgen overhead : 3550.39 -QPS w/o loadgen overhead : 3605.24 +QPS w/ loadgen overhead : 253.07 +QPS w/o loadgen overhead : 252.78 -Min latency (ns) : 269523 -Max latency (ns) : 1264151 -Mean latency (ns) : 277374 -50.00 percentile latency (ns) : 276206 -90.00 percentile latency (ns) : 282507 -95.00 percentile latency (ns) : 283951 -97.00 percentile latency (ns) : 285002 -99.00 percentile latency (ns) : 288229 -99.90 percentile latency (ns) : 303998 +Min latency (ns) : 266899 +Max latency (ns) : 9263318962 +Mean latency (ns) : 3956042 +50.00 percentile latency (ns) : 281927 +90.00 percentile latency (ns) : 300822 +95.00 percentile latency (ns) : 309027 +97.00 percentile latency (ns) : 320449 +99.00 percentile latency (ns) : 1472350 +99.90 percentile latency (ns) : 1060058821 ================================================ Test Parameters Used @@ -119,12 +119,12 @@ No warnings encountered during test. No errors encountered during test. Finished running actual test. Device Device:0.GPU processed: - 2130236 batches of size 1 + 151886 batches of size 1 Memcpy Calls: 0 PerSampleCudaMemcpy Calls: 0 - BatchedCudaMemcpy Calls: 2130236 + BatchedCudaMemcpy Calls: 151886 &&&& PASSED Default_Harness # ./build/bin/harness_default -[2024-12-24 23:29:00,872 run_harness.py:166 INFO] Result: result_90.00_percentile_latency_ns: 282507, Result is VALID +[2025-01-01 04:02:05,292 run_harness.py:166 INFO] Result: result_90.00_percentile_latency_ns: 300822, Result is VALID ======================== Result summaries: ======================== diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/system_info.txt b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/system_info.txt index c2bb3015d..45652e989 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/system_info.txt +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/system_info.txt @@ -2,10 +2,10 @@ Platform Details ------------------------------------------------------------ 1. uname -a -Linux 2a6a3464ad42 6.8.0-51-generic #52-Ubuntu SMP PREEMPT_DYNAMIC Thu Dec 5 13:09:44 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux +Linux bec71595fc42 6.8.0-51-generic #52-Ubuntu SMP PREEMPT_DYNAMIC Thu Dec 5 13:09:44 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux ------------------------------------------------------------ 2. w - 23:29:15 up 6 days, 9:22, 0 users, load average: 1.00, 1.11, 1.42 + 04:31:55 up 13 days, 14:24, 0 users, load average: 23.21, 23.57, 26.65 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT ------------------------------------------------------------ 3. Username @@ -40,7 +40,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 3308.364 +cpu MHz : 5373.998 cache size : 1024 KB physical id : 0 siblings : 32 @@ -68,7 +68,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5456.140 cache size : 1024 KB physical id : 0 siblings : 32 @@ -96,7 +96,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5279.906 cache size : 1024 KB physical id : 0 siblings : 32 @@ -124,7 +124,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5455.533 cache size : 1024 KB physical id : 0 siblings : 32 @@ -152,7 +152,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4374.716 cache size : 1024 KB physical id : 0 siblings : 32 @@ -180,7 +180,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5458.340 cache size : 1024 KB physical id : 0 siblings : 32 @@ -208,7 +208,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5452.415 cache size : 1024 KB physical id : 0 siblings : 32 @@ -236,7 +236,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5458.203 cache size : 1024 KB physical id : 0 siblings : 32 @@ -264,7 +264,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5246.167 cache size : 1024 KB physical id : 0 siblings : 32 @@ -292,7 +292,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5248.459 cache size : 1024 KB physical id : 0 siblings : 32 @@ -320,7 +320,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5247.372 cache size : 1024 KB physical id : 0 siblings : 32 @@ -348,7 +348,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5256.885 cache size : 1024 KB physical id : 0 siblings : 32 @@ -376,7 +376,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 3543.582 +cpu MHz : 5255.131 cache size : 1024 KB physical id : 0 siblings : 32 @@ -404,7 +404,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5219.044 cache size : 1024 KB physical id : 0 siblings : 32 @@ -432,7 +432,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 3941.550 +cpu MHz : 5250.132 cache size : 1024 KB physical id : 0 siblings : 32 @@ -460,7 +460,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 3652.943 +cpu MHz : 5212.606 cache size : 1024 KB physical id : 0 siblings : 32 @@ -488,7 +488,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5316.949 cache size : 1024 KB physical id : 0 siblings : 32 @@ -516,7 +516,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5441.231 cache size : 1024 KB physical id : 0 siblings : 32 @@ -544,7 +544,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5459.434 cache size : 1024 KB physical id : 0 siblings : 32 @@ -572,7 +572,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5394.149 cache size : 1024 KB physical id : 0 siblings : 32 @@ -600,7 +600,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5489.439 +cpu MHz : 4466.990 cache size : 1024 KB physical id : 0 siblings : 32 @@ -628,7 +628,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5461.086 cache size : 1024 KB physical id : 0 siblings : 32 @@ -656,7 +656,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5323.637 cache size : 1024 KB physical id : 0 siblings : 32 @@ -712,7 +712,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5046.858 cache size : 1024 KB physical id : 0 siblings : 32 @@ -740,7 +740,7 @@ model : 97 model name : AMD Ryzen 9 7950X 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name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5240.479 cache size : 1024 KB physical id : 0 siblings : 32 @@ -946,7 +946,7 @@ CPU family: 25 Model: 97 Model name: AMD Ryzen 9 7950X 16-Core Processor Stepping: 2 -CPU MHz: 5382.738 +CPU MHz: 5333.581 CPU max MHz: 5881.0000 CPU min MHz: 400.0000 BogoMIPS: 8982.90 @@ -976,49 +976,49 @@ Flags: fpu vme de pse tsc msr pae mce cx8 apic se available: 1 nodes (0) node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 node 0 size: 128007 MB -node 0 free: 33639 MB +node 0 free: 1137 MB node distances: node 0 0: 10 ------------------------------------------------------------ 9. /proc/meminfo MemTotal: 131080068 kB -MemFree: 34447052 kB -MemAvailable: 127387388 kB -Buffers: 2607264 kB -Cached: 88315604 kB -SwapCached: 118852 kB -Active: 28178408 kB -Inactive: 63093516 kB -Active(anon): 346764 kB -Inactive(anon): 40924 kB -Active(file): 27831644 kB -Inactive(file): 63052592 kB +MemFree: 1164096 kB +MemAvailable: 37818884 kB +Buffers: 38672 kB +Cached: 35969636 kB +SwapCached: 358192 kB +Active: 62934596 kB +Inactive: 61948392 kB +Active(anon): 44421312 kB +Inactive(anon): 44463304 kB +Active(file): 18513284 kB +Inactive(file): 17485088 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 683591672 kB -SwapFree: 683133832 kB +SwapFree: 86990740 kB Zswap: 0 kB Zswapped: 0 kB -Dirty: 21056 kB +Dirty: 21428 kB Writeback: 0 kB -AnonPages: 338452 kB -Mapped: 254716 kB -Shmem: 38592 kB -KReclaimable: 3303588 kB -Slab: 4026404 kB -SReclaimable: 3303588 kB -SUnreclaim: 722816 kB -KernelStack: 15952 kB -PageTables: 19528 kB +AnonPages: 88516248 kB +Mapped: 87688 kB +Shmem: 9936 kB +KReclaimable: 1905952 kB +Slab: 2440376 kB +SReclaimable: 1905952 kB +SUnreclaim: 534424 kB +KernelStack: 23440 kB +PageTables: 1437084 kB SecPageTables: 0 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 749131704 kB -Committed_AS: 4973320 kB +Committed_AS: 698832608 kB VmallocTotal: 34359738367 kB -VmallocUsed: 252564 kB +VmallocUsed: 262108 kB VmallocChunk: 0 kB Percpu: 38400 kB HardwareCorrupted: 0 kB @@ -1034,9 +1034,9 @@ HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB Hugetlb: 0 kB -DirectMap4k: 20566432 kB -DirectMap2M: 109676544 kB -DirectMap1G: 4194304 kB +DirectMap4k: 35742112 kB +DirectMap2M: 96598016 kB +DirectMap1G: 2097152 kB ------------------------------------------------------------ 10. who -r ------------------------------------------------------------ @@ -1290,16 +1290,16 @@ dev.tty.ldisc_autoload = 1 dev.tty.legacy_tiocsti = 0 fs.aio-max-nr = 65536 fs.aio-nr = 0 -fs.dentry-state = 1301967 890792 45 0 213976 0 +fs.dentry-state = 538377 333454 45 0 71076 0 fs.dir-notify-enable = 1 fs.epoll.max_user_watches = 29163675 fs.fanotify.max_queued_events = 16384 fs.fanotify.max_user_groups = 128 fs.fanotify.max_user_marks = 1048576 fs.file-max = 9223372036854775807 -fs.file-nr = 5568 0 9223372036854775807 -fs.inode-nr = 1102325 15671 -fs.inode-state = 1102325 15671 0 0 0 0 0 +fs.file-nr = 5760 0 9223372036854775807 +fs.inode-nr = 656756 191888 +fs.inode-state = 656756 191888 0 0 0 0 0 fs.inotify.max_queued_events = 16384 fs.inotify.max_user_instances = 128 fs.inotify.max_user_watches = 65536 @@ -1327,7 +1327,7 @@ fs.quota.drops = 0 fs.quota.free_dquots = 0 fs.quota.lookups = 0 fs.quota.reads = 0 -fs.quota.syncs = 540 +fs.quota.syncs = 782 fs.quota.writes = 0 fs.suid_dumpable = 2 fs.verity.require_signatures = 0 @@ -1354,7 +1354,7 @@ kernel.ftrace_dump_on_oops = 0 kernel.ftrace_enabled = 1 kernel.hardlockup_all_cpu_backtrace = 0 kernel.hardlockup_panic = 0 -kernel.hostname = 2a6a3464ad42 +kernel.hostname = bec71595fc42 kernel.hotplug = kernel.hung_task_all_cpu_backtrace = 0 kernel.hung_task_check_count = 4194304 @@ -1386,7 +1386,7 @@ kernel.msgmnb = 16384 kernel.msgmni = 32000 kernel.ngroups_max = 65536 kernel.nmi_watchdog = 1 -kernel.ns_last_pid = 11234 +kernel.ns_last_pid = 11267 kernel.numa_balancing = 0 kernel.numa_balancing_promote_rate_limit_MBps = 65536 kernel.oops_all_cpu_backtrace = 0 @@ -1417,13 +1417,13 @@ kernel.printk_devkmsg = on kernel.printk_ratelimit = 5 kernel.printk_ratelimit_burst = 10 kernel.pty.max = 4096 -kernel.pty.nr = 10 +kernel.pty.nr = 20 kernel.pty.reserve = 1024 kernel.random.boot_id = d972d8ae-c9e1-46e1-875d-9f419475517a kernel.random.entropy_avail = 256 kernel.random.poolsize = 256 kernel.random.urandom_min_reseed_secs = 60 -kernel.random.uuid = 6f8b0ec7-71f3-4569-8471-e0d84fd57aad +kernel.random.uuid = 727d7327-e1cf-428d-9afe-d839eed7bd80 kernel.random.write_wakeup_threshold = 256 kernel.randomize_va_space = 2 kernel.real-root-dev = 0 @@ -2243,7 +2243,7 @@ loop17 7:17 0 65.5M 1 loop loop18 7:18 0 10.8M 1 loop loop19 7:19 0 89.4M 1 loop loop20 7:20 0 91.7M 1 loop -loop22 7:22 0 89.4M 1 loop +loop21 7:21 0 89.4M 1 loop loop23 7:23 0 9.1M 1 loop loop24 7:24 0 150.6M 1 loop loop25 7:25 0 10.8M 1 loop diff --git a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/system_info.txt b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/system_info.txt index 3095eb4c4..c8f3efccc 100644 --- a/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/system_info.txt +++ b/open/MLCommons/measurements/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/system_info.txt @@ -2,10 +2,10 @@ Platform Details ------------------------------------------------------------ 1. uname -a -Linux 2a6a3464ad42 6.8.0-51-generic #52-Ubuntu SMP PREEMPT_DYNAMIC Thu Dec 5 13:09:44 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux +Linux bec71595fc42 6.8.0-51-generic #52-Ubuntu SMP PREEMPT_DYNAMIC Thu Dec 5 13:09:44 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux ------------------------------------------------------------ 2. w - 00:03:03 up 6 days, 9:55, 0 users, load average: 1.00, 1.00, 1.01 + 09:35:24 up 13 days, 19:28, 0 users, load average: 8.74, 19.69, 28.50 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT ------------------------------------------------------------ 3. Username @@ -40,7 +40,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 4753.752 +cpu MHz : 5386.893 cache size : 1024 KB physical id : 0 siblings : 32 @@ -68,7 +68,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5419.996 +cpu MHz : 5396.848 cache size : 1024 KB physical id : 0 siblings : 32 @@ -96,7 +96,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5459.536 cache size : 1024 KB physical id : 0 siblings : 32 @@ -124,7 +124,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5192.384 cache size : 1024 KB physical id : 0 siblings : 32 @@ -152,7 +152,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5461.723 cache size : 1024 KB physical id : 0 siblings : 32 @@ -180,7 +180,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5463.467 cache size : 1024 KB physical id : 0 siblings : 32 @@ -208,7 +208,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4957.065 cache size : 1024 KB physical id : 0 siblings : 32 @@ -292,7 +292,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5204.928 cache size : 1024 KB physical id : 0 siblings : 32 @@ -320,7 +320,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4253.626 cache size : 1024 KB physical id : 0 siblings : 32 @@ -348,7 +348,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5239.767 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -404,7 +404,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 3506.855 +cpu MHz : 5263.494 cache size : 1024 KB physical id : 0 siblings : 32 @@ -432,7 +432,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 3476.715 cache size : 1024 KB physical id : 0 siblings : 32 @@ -460,7 +460,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 4298.874 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -516,7 +516,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5380.857 cache size : 1024 KB physical id : 0 siblings : 32 @@ -544,7 +544,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5450.968 cache size : 1024 KB physical id : 0 siblings : 32 @@ -628,7 +628,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 4765.247 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -656,7 +656,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 4247.876 +cpu MHz : 5379.315 cache size : 1024 KB physical id : 0 siblings : 32 @@ -684,7 +684,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4660.032 cache size : 1024 KB physical id : 0 siblings : 32 @@ -740,7 +740,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 3482.129 +cpu MHz : 400.000 cache size : 1024 KB physical id : 0 siblings : 32 @@ -824,7 +824,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5195.019 cache size : 1024 KB physical id : 0 siblings : 32 @@ -852,7 +852,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 5141.377 +cpu MHz : 5327.219 cache size : 1024 KB physical id : 0 siblings : 32 @@ -880,7 +880,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 4908.013 cache size : 1024 KB physical id : 0 siblings : 32 @@ -908,7 +908,7 @@ model : 97 model name : AMD Ryzen 9 7950X 16-Core Processor stepping : 2 microcode : 0xa601206 -cpu MHz : 400.000 +cpu MHz : 5264.552 cache size : 1024 KB physical id : 0 siblings : 32 @@ -946,7 +946,7 @@ CPU family: 25 Model: 97 Model name: AMD Ryzen 9 7950X 16-Core Processor Stepping: 2 -CPU MHz: 400.000 +CPU MHz: 5386.893 CPU max MHz: 5881.0000 CPU min MHz: 400.0000 BogoMIPS: 8982.90 @@ -976,49 +976,49 @@ Flags: fpu vme de pse tsc msr pae mce cx8 apic se available: 1 nodes (0) node 0 cpus: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 node 0 size: 128007 MB -node 0 free: 26383 MB +node 0 free: 4510 MB node distances: node 0 0: 10 ------------------------------------------------------------ 9. /proc/meminfo MemTotal: 131080068 kB -MemFree: 27016200 kB -MemAvailable: 127411576 kB -Buffers: 2615844 kB -Cached: 95736004 kB -SwapCached: 118936 kB -Active: 28190668 kB -Inactive: 70517720 kB -Active(anon): 354940 kB -Inactive(anon): 40532 kB -Active(file): 27835728 kB -Inactive(file): 70477188 kB +MemFree: 4617516 kB +MemAvailable: 61141648 kB +Buffers: 25260 kB +Cached: 57338976 kB +SwapCached: 16758280 kB +Active: 96513632 kB +Inactive: 25843660 kB +Active(anon): 58710880 kB +Inactive(anon): 6291144 kB +Active(file): 37802752 kB +Inactive(file): 19552516 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 683591672 kB -SwapFree: 683134856 kB +SwapFree: 549958132 kB Zswap: 0 kB Zswapped: 0 kB -Dirty: 40 kB +Dirty: 84 kB Writeback: 0 kB -AnonPages: 345448 kB -Mapped: 267664 kB -Shmem: 38932 kB -KReclaimable: 3329948 kB -Slab: 4054196 kB -SReclaimable: 3329948 kB -SUnreclaim: 724248 kB -KernelStack: 16192 kB -PageTables: 19320 kB +AnonPages: 64893896 kB +Mapped: 129836 kB +Shmem: 8952 kB +KReclaimable: 1425496 kB +Slab: 1942180 kB +SReclaimable: 1425496 kB +SUnreclaim: 516684 kB +KernelStack: 21552 kB +PageTables: 387332 kB SecPageTables: 0 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 749131704 kB -Committed_AS: 4981440 kB +Committed_AS: 190620176 kB VmallocTotal: 34359738367 kB -VmallocUsed: 252868 kB +VmallocUsed: 260412 kB VmallocChunk: 0 kB Percpu: 38400 kB HardwareCorrupted: 0 kB @@ -1034,9 +1034,9 @@ HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB Hugetlb: 0 kB -DirectMap4k: 20603296 kB -DirectMap2M: 109639680 kB -DirectMap1G: 4194304 kB +DirectMap4k: 36438432 kB +DirectMap2M: 95901696 kB +DirectMap1G: 2097152 kB ------------------------------------------------------------ 10. who -r ------------------------------------------------------------ @@ -1290,16 +1290,16 @@ dev.tty.ldisc_autoload = 1 dev.tty.legacy_tiocsti = 0 fs.aio-max-nr = 65536 fs.aio-nr = 0 -fs.dentry-state = 1327447 912860 45 0 220822 0 +fs.dentry-state = 214380 118744 45 0 8605 0 fs.dir-notify-enable = 1 fs.epoll.max_user_watches = 29163675 fs.fanotify.max_queued_events = 16384 fs.fanotify.max_user_groups = 128 fs.fanotify.max_user_marks = 1048576 fs.file-max = 9223372036854775807 -fs.file-nr = 5312 0 9223372036854775807 -fs.inode-nr = 1120945 15671 -fs.inode-state = 1120945 15671 0 0 0 0 0 +fs.file-nr = 6208 0 9223372036854775807 +fs.inode-nr = 270939 64136 +fs.inode-state = 270939 64136 0 0 0 0 0 fs.inotify.max_queued_events = 16384 fs.inotify.max_user_instances = 128 fs.inotify.max_user_watches = 65536 @@ -1327,7 +1327,7 @@ fs.quota.drops = 0 fs.quota.free_dquots = 0 fs.quota.lookups = 0 fs.quota.reads = 0 -fs.quota.syncs = 540 +fs.quota.syncs = 784 fs.quota.writes = 0 fs.suid_dumpable = 2 fs.verity.require_signatures = 0 @@ -1354,7 +1354,7 @@ kernel.ftrace_dump_on_oops = 0 kernel.ftrace_enabled = 1 kernel.hardlockup_all_cpu_backtrace = 0 kernel.hardlockup_panic = 0 -kernel.hostname = 2a6a3464ad42 +kernel.hostname = bec71595fc42 kernel.hotplug = kernel.hung_task_all_cpu_backtrace = 0 kernel.hung_task_check_count = 4194304 @@ -1386,7 +1386,7 @@ kernel.msgmnb = 16384 kernel.msgmni = 32000 kernel.ngroups_max = 65536 kernel.nmi_watchdog = 1 -kernel.ns_last_pid = 18592 +kernel.ns_last_pid = 18625 kernel.numa_balancing = 0 kernel.numa_balancing_promote_rate_limit_MBps = 65536 kernel.oops_all_cpu_backtrace = 0 @@ -1417,13 +1417,13 @@ kernel.printk_devkmsg = on kernel.printk_ratelimit = 5 kernel.printk_ratelimit_burst = 10 kernel.pty.max = 4096 -kernel.pty.nr = 10 +kernel.pty.nr = 19 kernel.pty.reserve = 1024 kernel.random.boot_id = d972d8ae-c9e1-46e1-875d-9f419475517a kernel.random.entropy_avail = 256 kernel.random.poolsize = 256 kernel.random.urandom_min_reseed_secs = 60 -kernel.random.uuid = be38938a-9f92-4991-bacc-f38cdd418843 +kernel.random.uuid = c7e69430-7a55-4c5f-943c-1489bc69196e kernel.random.write_wakeup_threshold = 256 kernel.randomize_va_space = 2 kernel.real-root-dev = 0 @@ -2243,7 +2243,7 @@ loop17 7:17 0 65.5M 1 loop loop18 7:18 0 10.8M 1 loop loop19 7:19 0 89.4M 1 loop loop20 7:20 0 91.7M 1 loop -loop22 7:22 0 89.4M 1 loop +loop21 7:21 0 89.4M 1 loop loop23 7:23 0 9.1M 1 loop loop24 7:24 0 150.6M 1 loop loop25 7:25 0 10.8M 1 loop diff --git a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/accuracy/mlperf_log_detail.txt b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/accuracy/mlperf_log_detail.txt index 5b5211d12..8e69a81da 100644 --- a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/accuracy/mlperf_log_detail.txt +++ b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/accuracy/mlperf_log_detail.txt @@ -1,646 +1,646 @@ -:::MLLOG {"key": "loadgen_version", "value": "4.0 @ 486a629ea4", "time_ms": 0.002985, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/version.cc", "line_no": 53, "pid": 26667, "tid": 26667}} -:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-12-24T23:17:13.606348", "time_ms": 0.002985, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/version.cc", "line_no": 55, "pid": 26667, "tid": 26667}} -:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-12-25T07:17:13.606351", "time_ms": 0.002985, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/version.cc", "line_no": 56, "pid": 26667, "tid": 26667}} -:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-02-15T15:46:50-05:00", "time_ms": 0.002985, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/version.cc", "line_no": 57, "pid": 26667, "tid": 26667}} -:::MLLOG {"key": "loadgen_git_log_message", "value": "486a629ea4d5c5150f452d0b0a196bf71fd2021e Hotfix: DLRMv2 Audit Test01 fallback failure (#1626)\nf9a643c0a0e920588da1b51a1d822e1071a9dbec Add number of tokens to offline (#1623)\nf06b920eac2170df38b5502c7443f50c9afa6045 Bugfix: equal-issue mode on offline causing accuracy run to fail (3D-UNet) (#1624)\n0ed5190e82e1ca1cf95626e50e61cb6678c7f2ff Fix submission checker and TEST06 for Llama2 (#1616)\n817dd961221d3ca284b024368130bd5dc5e4b54a Turn equal issue mode off for TEST06 (#1615)\n840435a1abe8be823e0a5a18ad3173bc520aa24f Update README.md with CM commands to download stable-diffusion, gptj and dlrmv2 models (#1604)\n3190d09a148bc1d72c9d946e4cf3b54db0d0e60a Typo fix in README.md (#1588)\nb0777f0bd3b7e5cd6a51d670d8b4df656cf6fb29 Update README.md - remove unwanted lines in CM commands (#1601)\nd7dba0826ac96a0e8bcae525086961e47c409a38 Remove loadgen warnings (#1608)\nd45a66c33bb0b6548d6172b38645bf94ffe24b39 Add upper limit to tokens per sample 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+:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 494413, "time_ms": 611104.328477, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 25145, "tid": 25145}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 551560, "time_ms": 611104.328477, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 25145, "tid": 25145}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 790777, "time_ms": 611104.328477, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 25145, "tid": 25145}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 2956252, "time_ms": 611104.328477, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 25145, "tid": 25145}} diff --git a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/performance/run_1/mlperf_log_summary.txt index 835a33831..78892de70 100644 --- a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/performance/run_1/mlperf_log_summary.txt +++ b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/multistream/performance/run_1/mlperf_log_summary.txt @@ -4,29 +4,29 @@ MLPerf Results Summary SUT name : LWIS_Server Scenario : MultiStream Mode : PerformanceOnly -99th percentile latency (ns) : 457564 +99th percentile latency (ns) : 790777 Result is : VALID Min duration satisfied : Yes Min queries satisfied : Yes Early stopping satisfied: Yes Early Stopping Result: - * Processed at least 662 queries (1336340). - * Would discard 13095 highest latency queries. - * Early stopping 99th percentile estimate: 457694 + * Processed at least 662 queries (1272080). + * Would discard 12458 highest latency queries. + * Early stopping 99th percentile estimate: 798611 ================================================ Additional Stats ================================================ Per-query latency: -Min latency (ns) : 433289 -Max latency (ns) : 1487258 -Mean latency (ns) : 444464 -50.00 percentile latency (ns) : 443509 -90.00 percentile latency (ns) : 449059 -95.00 percentile latency (ns) : 451323 -97.00 percentile latency (ns) : 453617 -99.00 percentile latency (ns) : 457564 -99.90 percentile latency (ns) : 465790 +Min latency (ns) : 430884 +Max latency (ns) : 357813780 +Mean latency (ns) : 465760 +50.00 percentile latency (ns) : 446123 +90.00 percentile latency (ns) : 475468 +95.00 percentile latency (ns) : 494413 +97.00 percentile latency (ns) : 551560 +99.00 percentile latency (ns) : 790777 +99.90 percentile latency (ns) : 2956252 ================================================ Test Parameters Used diff --git a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/accuracy/mlperf_log_detail.txt b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/accuracy/mlperf_log_detail.txt index 61b2a4bb9..5b01c1ed3 100644 --- a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/accuracy/mlperf_log_detail.txt +++ b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/accuracy/mlperf_log_detail.txt @@ -1,644 +1,644 @@ -:::MLLOG {"key": "loadgen_version", "value": "4.0 @ 486a629ea4", "time_ms": 0.003136, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/version.cc", "line_no": 53, "pid": 19801, "tid": 19801}} -:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-12-24T23:17:13.606348", "time_ms": 0.003136, "namespace": "mlperf::logging", "event_type": 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"time_ms": 7885103.781854, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 18280, "tid": 18280}} diff --git a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/performance/run_1/mlperf_log_summary.txt index c54054197..912b4fcf6 100644 --- a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/performance/run_1/mlperf_log_summary.txt +++ b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/offline/performance/run_1/mlperf_log_summary.txt @@ -4,7 +4,7 @@ MLPerf Results Summary SUT name : LWIS_Server Scenario : Offline Mode : PerformanceOnly -Samples per second: 44354.9 +Samples per second: 3633.97 Result is : VALID Min duration satisfied : Yes Min queries satisfied : Yes @@ -13,15 +13,15 @@ Result is : VALID ================================================ Additional Stats ================================================ -Min latency (ns) : 185345230 -Max latency (ns) : 645627546417 -Mean latency (ns) : 322655572323 -50.00 percentile latency (ns) : 322603993114 -90.00 percentile latency (ns) : 581023033737 -95.00 percentile latency (ns) : 613325298535 -97.00 percentile latency (ns) : 626246842386 -99.00 percentile latency (ns) : 639168446304 -99.90 percentile latency (ns) : 644982685357 +Min latency (ns) : 212501451 +Max latency (ns) : 7880286936177 +Mean latency (ns) : 640135971137 +50.00 percentile latency (ns) : 5045376227510 +90.00 percentile latency (ns) : 7815701597962 +95.00 percentile latency (ns) : 7848065465747 +97.00 percentile latency (ns) : 7860943299479 +99.00 percentile latency (ns) : 7873842420964 +99.90 percentile latency (ns) : 7879643297455 ================================================ Test Parameters Used @@ -46,6 +46,6 @@ performance_issue_same : 0 performance_issue_same_index : 0 performance_sample_count : 1024 -No warnings encountered during test. +1 warning encountered. See detailed log. No errors encountered during test. diff --git a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/accuracy/mlperf_log_detail.txt b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/accuracy/mlperf_log_detail.txt index baa6c90f9..f298d81fb 100644 --- a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/accuracy/mlperf_log_detail.txt +++ b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/accuracy/mlperf_log_detail.txt @@ -1,651 +1,651 @@ -:::MLLOG {"key": "loadgen_version", "value": "4.0 @ 486a629ea4", "time_ms": 0.011241, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/version.cc", "line_no": 53, "pid": 34071, 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100644 --- a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/performance/run_1/mlperf_log_summary.txt +++ b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/server/performance/run_1/mlperf_log_summary.txt @@ -18,15 +18,15 @@ Additional Stats ================================================ Completed samples per second : 35357.75 -Min latency (ns) : 1721793 -Max latency (ns) : 239395333 -Mean latency (ns) : 3005541 -50.00 percentile latency (ns) : 2827351 -90.00 percentile latency (ns) : 3573039 -95.00 percentile latency (ns) : 3711462 -97.00 percentile latency (ns) : 3788290 -99.00 percentile latency (ns) : 3902820 -99.90 percentile latency (ns) : 75657243 +Min latency (ns) : 1719085 +Max latency (ns) : 110662823 +Mean latency (ns) : 2886657 +50.00 percentile latency (ns) : 2819887 +90.00 percentile latency (ns) : 3566001 +95.00 percentile latency (ns) : 3704432 +97.00 percentile latency (ns) : 3781485 +99.00 percentile latency (ns) : 3897364 +99.90 percentile latency (ns) : 22255064 ================================================ Test Parameters Used diff --git a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/accuracy/mlperf_log_detail.txt b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/accuracy/mlperf_log_detail.txt index b0a0c27f9..71727c2d7 100644 --- a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/accuracy/mlperf_log_detail.txt +++ b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/accuracy/mlperf_log_detail.txt @@ -1,645 +1,645 @@ -:::MLLOG {"key": "loadgen_version", "value": "4.0 @ 486a629ea4", "time_ms": 0.012533, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": 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{"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/logging.cc", "line_no": 898, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 1023312.678158, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/logging.cc", "line_no": 900, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 1023312.678158, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/logging.cc", "line_no": 902, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 1023312.678158, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/logging.cc", "line_no": 904, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 1023312.678158, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/logging.cc", "line_no": 906, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 1023312.678158, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/logging.cc", "line_no": 908, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "power_begin", "value": "01-01-2025 11:52:02.255", "time_ms": 1023312.678980, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/loadgen.cc", "line_no": 564, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "power_end", "value": "01-01-2025 12:02:04.013", "time_ms": 1023312.678980, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/loadgen.cc", "line_no": 566, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_validity", "value": "VALID", "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 644, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_min_duration_met", "value": true, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 649, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_min_queries_met", "value": true, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 650, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "early_stopping_met", "value": true, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 651, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "early_stopping_result", "value": " * Processed at least 64 queries (151886). * Would discard 14915 highest latency queries. * Early stopping 90th percentile estimate: 300962 * Early stopping 99th percentile estimate: 1789992", "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 669, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_query_count", "value": 151886, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 679, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_qps_with_loadgen_overhead", "value": 253.074, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 702, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_qps_without_loadgen_overhead", "value": 252.778, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 703, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "early_stopping_latency_ss", "value": 300962, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 704, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "early_stopping_latency_ms", "value": 1789992, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 706, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_min_latency_ns", "value": 266899, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 741, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_max_latency_ns", "value": 9263318962, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 742, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_mean_latency_ns", "value": 3956042, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 743, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 281927, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 300822, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 309027, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 320449, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 1472350, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 9724, "tid": 9724}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 1060058821, "time_ms": 1023590.190218, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "/home/cmuser/CM/repos/local/cache/ba8d5f2a6bc546f9/repo/closed/NVIDIA/build/inference/loadgen/results.cc", "line_no": 745, "pid": 9724, "tid": 9724}} diff --git a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/performance/run_1/mlperf_log_summary.txt index 79999a607..5450e373b 100644 --- a/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/performance/run_1/mlperf_log_summary.txt +++ b/open/MLCommons/results/RTX4090x1-nvidia_original-gpu-tensorrt-vdefault-default_config/resnet50/singlestream/performance/run_1/mlperf_log_summary.txt @@ -4,32 +4,32 @@ MLPerf Results Summary SUT name : LWIS_Server Scenario : SingleStream Mode : PerformanceOnly -90th percentile latency (ns) : 282507 +90th percentile latency (ns) : 300822 Result is : VALID Min duration satisfied : Yes Min queries satisfied : Yes Early stopping satisfied: Yes Early Stopping Result: - * Processed at least 64 queries (2130236). - * Would discard 212004 highest latency queries. - * Early stopping 90th percentile estimate: 282518 - * Early stopping 99th percentile estimate: 288269 + * Processed at least 64 queries (151886). + * Would discard 14915 highest latency queries. + * Early stopping 90th percentile estimate: 300962 + * Early stopping 99th percentile estimate: 1789992 ================================================ Additional Stats ================================================ -QPS w/ loadgen overhead : 3550.39 -QPS w/o loadgen overhead : 3605.24 +QPS w/ loadgen overhead : 253.07 +QPS w/o loadgen overhead : 252.78 -Min latency (ns) : 269523 -Max latency (ns) : 1264151 -Mean latency (ns) : 277374 -50.00 percentile latency (ns) : 276206 -90.00 percentile latency (ns) : 282507 -95.00 percentile latency (ns) : 283951 -97.00 percentile latency (ns) : 285002 -99.00 percentile latency (ns) : 288229 -99.90 percentile latency (ns) : 303998 +Min latency (ns) : 266899 +Max latency (ns) : 9263318962 +Mean latency (ns) : 3956042 +50.00 percentile latency (ns) : 281927 +90.00 percentile latency (ns) : 300822 +95.00 percentile latency (ns) : 309027 +97.00 percentile latency (ns) : 320449 +99.00 percentile latency (ns) : 1472350 +99.90 percentile latency (ns) : 1060058821 ================================================ Test Parameters Used