Understanding Performance Portability of Bioinformatics Applications in SYCL on an NVIDIA GPU
Zheming Jin, Jeffrey S. Vetter
20222022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)17 citationsDOIOpen Access PDF
Abstract
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.
Topics & Concepts
Software portabilityCUDAComputer scienceProfiling (computer programming)General-purpose computing on graphics processing unitsParallel computingSupercomputerComputer architectureBioinformaticsOperating systemGraphicsBiologyGene expression and cancer classificationGenomics and Phylogenetic StudiesMachine Learning in Bioinformatics