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Non-Conventional AMD GPU Characterization Tool and Methodology

Set of benchmarks ana analysis tools to characterize the response of AMD GPU architecture to different workloads whily using non-conventional (extreme undervoltage) DVFS settings

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites (for CentOS 7.0)

  • Python 3.8
  • Anaconda/Miniconda enviroment
  • ROCm 3.0
  • ROCblas
  • MIopen-hip
  • MIopen-gemm

Installing

  • Create conda enviroment for analysis tool
conda env create -f environment/environment.yml
  • ROCm 3.0
sudo yum install rocm-dkms rock-dkms
sudo yum install rocblas
sudo yum install miopen-hip
sudo yum install miopengemm

Running the tests

Use the exploreBenchmark Python script to run a Benchmark on different GPU DVFS configurations

General example for running benchmark

python exploreBenchmark.py -b <location of executable file> -e -c -v -t 10 -lc 7 --step 25 --reset --config <configuration file>

Example for running SFU benchmark

python exploreBenchmark.py -b Benchmarks/Core/ALU/SFU/Float/sp/eventPerformance_SFU_Float_sp -e -c -v -t 10 -lc 7 --step 25 --reset --config configExploreFiles/11.txt

Runing analysis tool

python analysisBenchmark.py -p <location of results files> -c <config file>

Built With

  • Python - For running and analysis script
  • C++ - Benchmarks
  • HIP - AMD Kernels

Authors

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

  • Hat tip to anyone whose code was used
  • Inspiration
  • The professors Nuno Roma and Pedro Tomás for all the discussion and debate over computer architecture