HAMPPSterS: Hybrid PC-HPC Automated Monitoring and Post-processing: Parametric Study Scheduler for Simulations

Overview

HAMPPSterS is a Python-based repository designed to facilitate the orchestration of simulations in a hybrid environment, utilising both a local PC and a remote High-Performance Computing (HPC) system. This tool streamlines the simulation workflow, covering parametric run generation, job submission, monitoring, convergence checks, restarting, file conversion, and post-processing.

Features

1. Parametric Run Generation

   • Utilises Design of Experiments (DOE) Latin Hypercube Sampling (LHS) to create a parametric run based on a defined sample space.

2. Remote HPC Job Submission

   • Sets up and submits simulation runs on a remote HPC system using the provided job.sh script.

3. Job Monitoring and Convergence Checks

   • Monitors the status of the HPC job during queuing and execution.
   • Executes scheduled convergence checks to ensure simulation progress.

4. Automatic Job Restarting

   • Verifies restarting conditions and re-submits the job accordingly.
   • Restarts the monitoring loop to ensure continuous progress.

5. File Conversion

   • Converts simulation files from VTK to VTR format upon job completion.

6. Local Post-Processing

   • Transfers final converted files to the local PC.
   • Executes post-processing operations using PvPython to obtain desired outputs.

Getting Started

1. Clone the repository:

   git clone https://github.com/jpv219/HAMPPSterS.git
   
   conda create --name your_environment_name --file requirements.txt
   

Contact

• [email protected] - Juan Pablo Valdes
• [email protected] - Paula Pico
• [email protected] - Fuyue Liang