JAWS: A JavaScript framework for adaptive CPU-GPU work sharing

Xianglan Piao, Channoh Kim, Younghwan Oh, Huiying Li, Jincheon Kim, Hanjun Kim, Jae W. Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper introduces JAWS, a JavaScript framework for adaptive work sharing between CPU and GPU for data-parallel workloads. Unlike conventional heterogeneous parallel programming environments for JavaScript, which use only one compute device when executing a single kernel, JAWS accelerates kernel execution by exploiting both devices to realize full performance potential of heterogeneous multicores. JAWS employs an efficient work partitioning algorithm that finds an optimal work distribution between the two devices without requiring offline profiling. The JAWS runtime provides shared arrays for multiple parallel contexts, hence eliminating extra copy overhead for input and output data. Our preliminary evaluation with both CPU-friendly and GPU-friendly benchmarks demonstrates that JAWS provides good load balancing and efficient data communication between parallel contexts, to significantly outperform best single-device execution.

Original languageEnglish
Title of host publication20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2015 - Proceedings
PublisherAssociation for Computing Machinery
Pages251-252
Number of pages2
ISBN (Electronic)9781450332057
DOIs
Publication statusPublished - 2015 Jan 24
Event20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2015 - San Francisco, United States
Duration: 2015 Feb 72015 Feb 11

Publication series

NameProceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP
Volume2015-January

Other

Other20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2015
CountryUnited States
CitySan Francisco
Period15/2/715/2/11

All Science Journal Classification (ASJC) codes

  • Software

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  • Cite this

    Piao, X., Kim, C., Oh, Y., Li, H., Kim, J., Kim, H., & Lee, J. W. (2015). JAWS: A JavaScript framework for adaptive CPU-GPU work sharing. In 20th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2015 - Proceedings (pp. 251-252). (Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP; Vol. 2015-January). Association for Computing Machinery. https://doi.org/10.1145/2688500.2688525