Understanding Performance Portability of Bioinformatics Applications in SYCL on an NVIDIA GPU

Jin, Zheming; Vetter, Jeffrey

doi:10.1109/BIBM55620.2022.9995222

Understanding Performance Portability of Bioinformatics Applications in SYCL on an NVIDIA GPU

Conference · Wed Nov 30 23:00:00 EST 2022

DOI:https://doi.org/10.1109/BIBM55620.2022.9995222· OSTI ID:1909099

Jin, Zheming ^[1]; ^[1]

ORNL

Our goal is to have a better understanding of performance portability of SYCL kernels on a GPU. Toward this goal, we migrate representative kernels in bioinformatics applications from CUDA to SYCL, evaluate their performance on an NVIDIA GPU, and explain the performance gaps through performance profiling and analyses. We hope that the findings provide valuable feedback to the development of the SYCL ecosystem.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE; USDOE Office of Science (SC)

DOE Contract Number:: AC05-00OR22725

OSTI ID:: 1909099

Country of Publication:: United States

Language:: English

References (24)

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