Porting Numerical Integration Codes from CUDA to oneAPI: A Case Study
Herein, we present our experience in porting optimized CUDA implementations to oneAPI. We focus on the use case of numerical integration, particularly the CUDA implementations of PAGANI and $$m$$-Cubes. We faced several challenges that caused performance degradation in the oneAPI ports. These include differences in utilized registers per thread, compiler optimizations, and mappings of CUDA library calls to oneAPI equivalents. After addressing those challenges, we tested both the PAGANI and m-Cubes integrators on numerous integrands of various characteristics. To evaluate the quality of the ports, we collected performance metrics of the CUDA and oneAPI implementations on the Nvidia V100 GPU. We found that the oneAPI ports often achieve comparable performance to the CUDA versions, and that they are at most 10% slower.
- Research Organization:
- Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), High Energy Physics (HEP)
- Grant/Contract Number:
- AC02-07CH11359; AC05-06OR23177; AC02-06CH11357
- OSTI ID:
- 1969670
- Report Number(s):
- FERMILAB-CONF-23-007-LDRD-SCD; arXiv:2302.05730; oai:inspirehep.net:2643005; TRN: US2313429
- Journal Information:
- Lecture Notes in Computer Science, Conference: 38th International Conference, ISC High Performance 2023, Hamburg (Germany), May 21-25 2023; ISSN 0302-9743
- Publisher:
- SpringerCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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