This repository contains the coursework for the Concurrent and Parallel Systems module. The module focuses on developing skills in designing, implementing, and evaluating concurrent and parallel systems using C++ and other relevant tools. The coursework is divided into two main projects:
Both projects emphasize parallelization techniques and require a detailed report accompanying the implementation.
Objective: Develop a C++ application that sorts images by color temperature based on their median hue. The sorting process must be progressive to maintain a smooth user experience.
Key Requirements:
- Convert images from RGB to HSV color space and compute the median hue.
- Sort images progressively, ensuring the UI remains responsive.
- Implement parallelism to handle image loading, processing, and sorting in background threads.
- Programming Language: C++
- Libraries: Use
stb_imagefor image loading. - Performance Measurement: Compare the startup and sorting times with and without parallelization.
- Analysis: Identify parallelizable tasks and shared resources.
- Methodology: Justify the chosen parallelization techniques.
- Results: Evaluate performance, include hardware setup, and present findings with graphs.
Objective: Modify an existing N-Queens problem implementation to run in parallel using OpenMP and GPU (CUDA/OpenCL).
Key Requirements:
- Reformulate the recursive N-Queens algorithm to work without recursion.
- Implement and compare three variations: Serial, OpenMP, and GPU.
- Measure and compare the performance of each approach for different values of N.
- Programming Language: C++
- Parallelization Tools: OpenMP for CPU parallelism, CUDA/OpenCL for GPU parallelism.
- Performance Measurement: Compare execution times across serial, OpenMP, and GPU implementations.
- OpenMP Implementation: Describe the parallelization approach, results, and any variants tested.
- GPU Implementation: Detail the GPU-based parallelization, results, and any tested configurations.
- Overall Findings: Compare and discuss the three approaches, including hardware setup and performance graphs.