A Microbenchmark Framework for Performance Evaluation of OpenMP Target Offloading
Brookhaven National Laboratory, NY, USA
arXiv:2503.00408 [cs.PF], (1 Mar 2025)
@misc{atif2025microbenchmarkframeworkperformanceevaluation,
title={A Microbenchmark Framework for Performance Evaluation of OpenMP Target Offloading},
author={Mohammad Atif and Tianle Wang and Zhihua Dong and Charles Leggett and Meifeng Lin},
year={2025},
eprint={2503.00408},
archivePrefix={arXiv},
primaryClass={cs.PF},
url={https://arxiv.org/abs/2503.00408}
}
We present a framework based on Catch2 to evaluate performance of OpenMP’s target offload model via micro-benchmarks. The compilers supporting OpenMP’s target offload model for heterogeneous architectures are currently undergoing rapid development. These developments influence performance of various complex applications in different ways. This framework can be employed to track the impact of compiler upgrades and compare their performance with the native programming models. We use the framework to benchmark performance of a few commonly used operations on leadership class supercomputers such as Perlmutter at National Energy Research Scientific Computing (NERSC) Center and Frontier at Oak Ridge Leadership Computing Facility (OLCF). Such a framework will be useful for compiler developers to gain insights into the overall impact of many small changes, as well as for users to decide which compilers and versions are expected to yield best performance for their applications.
March 10, 2025 by hgpu
