Understanding SYCL Portability for Pseudorandom Number Generation: A Case Study with Gene-Expression Connectivity Mapping

Zheming Jin, Jeffrey S. Vetter

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

Abstract

Towards the goal of improving functional and performance portability of SYCL, we study a bioinformatics application that has been accelerated with CUDA and fast pseudorandom number generation on a GPU. We describe the experience of migrating pseudorandom number generation from CUDA to SYCL, evaluate the performance of pseudorandom number generators using the CUDA random number generation library, suggest the support of the XORWOW pseudorandom number generator in the oneAPI math kernel library (oneMKL) interface for performance portability, and identify the performance gap using the MKL interface in SYCL that supports pseudorandom number generation with third-party libraries. We hope that the results are valuable for the development of the SYCL ecosystem.

Original languageEnglish
Title of host publication2023 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages295-298
Number of pages4
ISBN (Electronic)9798350311990
DOIs
StatePublished - 2023
Event2023 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2023 - St. Petersburg, United States
Duration: May 15 2023May 19 2023

Publication series

Name2023 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2023

Conference

Conference2023 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2023
Country/TerritoryUnited States
CitySt. Petersburg
Period05/15/2305/19/23

Funding

We appreciate the reviewers' criticisms. The research used resources at 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 ACKNOWLEDGMENT We appreciate the reviewers’ criticisms. The research used resources at 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.

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

    Keywords

    • Bioinformatics
    • Portability
    • Programming model
    • Pseudorandom number generation

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