Experience Deploying Graph Applications on GPUs with SYCL

Zheming Jin, Jeffrey S. Vetter

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

SYCL allows for deployment and use of accelerators across vendors' platforms. In this work, we describe the experience of deploying graph analytics on vendors' GPUs using SYCL. We contrast the CUDA and SYCL application programming interfaces by describing the experience of migrating the applications from CUDA to SYCL, evaluate the performance of the applications on NVIDIA and AMD GPUs, and explore performance improvement with device-level parallelism. The results show that the recent SYCL extensions facilitate functional portability, but improving code optimizations and resource usage for performance portability is needed in the compiler implementation.

Original languageEnglish
Title of host publication52nd International Conference on Parallel Processing, ICPP 2023 - Workshops Proceedings
PublisherAssociation for Computing Machinery
Pages30-39
Number of pages10
ISBN (Electronic)9798400708435
DOIs
StatePublished - Aug 7 2023
Event52nd International Conference on Parallel Processing, ICPP 2023 - Workshops Proceedings - Salt Lake City, United States
Duration: Aug 7 2023Aug 10 2023

Publication series

NameACM International Conference Proceeding Series

Conference

Conference52nd International Conference on Parallel Processing, ICPP 2023 - Workshops Proceedings
Country/TerritoryUnited States
CitySalt Lake City
Period08/7/2308/10/23

Funding

We appreciate the reviewers for their comments and ACM TAPS for their assistance. This research used resources of the Experimental Computing Lab at Oak Ridge National Laboratory. This research was supported by the US Department of Energy Advanced Scientific Computing Research program under Contract No. DE-AC05-00OR22725. This research used resources of the Experimental Computing Lab at Oak Ridge National Laboratory. This research was supported by the US Department of Energy Advanced Scientific Computing Research program under Contract No. DEAC05-00OR22725.

FundersFunder number
US Department of Energy Advanced Scientific Computing ResearchDE-AC05-00OR22725
Oak Ridge National Laboratory

    Keywords

    • GPUs
    • SYCL
    • portability

    Fingerprint

    Dive into the research topics of 'Experience Deploying Graph Applications on GPUs with SYCL'. Together they form a unique fingerprint.

    Cite this