28156

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

Zheming Jin, Jeffrey S. Vetter
Oak Ridge National Laboratory
The IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022

@inproceedings{jin2022understanding,

   title={Understanding Performance Portability of Bioinformatics Applications in SYCL on an NVIDIA GPU},

   author={Jin, Zheming and Vetter, Jeffrey S},

   booktitle={2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)},

   pages={2190–2195},

   year={2022},

   organization={IEEE}

}

Download Download (PDF)   View View   Source Source   Source codes Source codes

Package:

924

views

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.
No votes yet.
Please wait...

You must be logged in to post a comment.

Recent source codes

* * *

* * *

HGPU group © 2010-2025 hgpu.org

All rights belong to the respective authors

Contact us: