GPA

GPU Performance Advisor

GPA is a performance advisor for NVIDIA GPUs that suggests potential code optimization opportunities at a hierarchy of levels, including individual lines, loops, and functions. GPA uses data flow analysis to approximately attribute measured instruction stalls to their root causes and uses information about a program's structure and the GPU to match inefficiency patterns with suggestions for optimization. GPA estimates each optimization's speedup based on a PC sampling-based performance model.

Quick Start

git clone --recursive https://github.com/Jokeren/GPA.git && cd GPA
./bin/install.sh
./bin/bench.sh rodinia/bfs

Documentation

• Installation Guide
• User's Guide
• [Developer's Guide]

Papers

• K. Zhou, X. Meng, R. Sai, D. Grubisic and J. Mellor-Crummey, "An Automated Tool for Analysis and Tuning of GPU-accelerated Code in HPC Applications." IEEE Transactions on Parallel and Distributed Systems (TPDS) (2021).
• K. Zhou, X. Meng, R. Sai and J. Mellor-Crummey, "GPA: A GPU Performance Advisor Based on Instruction Sampling," 2021 IEEE/ACM International Symposium on Code Generation and Optimization (CGO), Seoul, Korea (South), 2021, pp. 115-125, doi: 10.1109/CGO51591.2021.9370339.