research-article

ParallelJS: An Execution Framework for JavaScript on Heterogeneous Systems

Authors:

Sudhakar YalamanchiliAuthors Info & Claims

GPGPU-7: Proceedings of Workshop on General Purpose Processing Using GPUs

Pages 72 - 80

https://doi.org/10.1145/2588768.2576788

Published: 01 March 2014 Publication History

Abstract

JavaScript has been recognized as one of the most widely used script languages. Optimizations of JavaScript engines on mainstream web browsers enable efficient execution of JavaScript programs on CPUs. However, running JavaScript applications on emerging heterogeneous architectures that feature massively parallel hardware such as GPUs has not been well studied.

This paper proposes a framework for flexible mapping of JavaScript onto heterogeneous systems that have both CPUs and GPUs. The framework includes a frontend compiler, a construct library and a runtime system. JavaScript programs written with high-level constructs are compiled to GPU binary code and scheduled to GPUs by the runtime. Experiments show that the proposed framework achieves up to 26.8x speedup executing JavaScript applications on parallel GPUs over a mainstream web browser that runs on CPUs.

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Cited By

Benmerar TMegherbi TKachouane MDeriche ROulebsir-Boumghar F(2021)Browser-Level Parallelism and Interactive Rendering APIs for Scalable Computation-Intensive SaaS: Application to Brain Diffusion MRIIEEE Transactions on Services Computing10.1109/TSC.2018.284735414:4(971-984)Online publication date: 1-Jul-2021
https://doi.org/10.1109/TSC.2018.2847354
Fumero JKotselidis CKell SMarr S(2018)Using compiler snippets to exploit parallelism on heterogeneous hardware: a Java reduction case studyProceedings of the 10th ACM SIGPLAN International Workshop on Virtual Machines and Intermediate Languages10.1145/3281287.3281292(16-25)Online publication date: 4-Nov-2018
https://dl.acm.org/doi/10.1145/3281287.3281292
Sapuan FSaw MCheah E(2018)General-Purpose Computation on GPUs in the Browser Using gpu.jsComputing in Science and Engineering10.1109/MCSE.2018.10816311620:1(33-42)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1109/MCSE.2018.108163116
Show More Cited By

Index Terms

ParallelJS: An Execution Framework for JavaScript on Heterogeneous Systems
1. Computer systems organization
  1. Architectures
    1. Parallel architectures
2. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language types

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Published In

cover image ACM Other conferences

GPGPU-7: Proceedings of Workshop on General Purpose Processing Using GPUs

March 2014

110 pages

ISBN:9781450327664

DOI:10.1145/2588768

Conference Chairs:
John Cavazos,
Xiang Gong,
David Kaeli

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 01 March 2014

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GPGPU-7

GPGPU-7: Seventh Workshop on General Purpose Processing Using GPUs

March 1, 2014

UT, Salt Lake City, USA

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GPGPU-7 Paper Acceptance Rate 12 of 27 submissions, 44%;

Overall Acceptance Rate 57 of 129 submissions, 44%

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Cited By

Benmerar TMegherbi TKachouane MDeriche ROulebsir-Boumghar F(2021)Browser-Level Parallelism and Interactive Rendering APIs for Scalable Computation-Intensive SaaS: Application to Brain Diffusion MRIIEEE Transactions on Services Computing10.1109/TSC.2018.284735414:4(971-984)Online publication date: 1-Jul-2021
https://doi.org/10.1109/TSC.2018.2847354
Fumero JKotselidis CKell SMarr S(2018)Using compiler snippets to exploit parallelism on heterogeneous hardware: a Java reduction case studyProceedings of the 10th ACM SIGPLAN International Workshop on Virtual Machines and Intermediate Languages10.1145/3281287.3281292(16-25)Online publication date: 4-Nov-2018
https://dl.acm.org/doi/10.1145/3281287.3281292
Sapuan FSaw MCheah E(2018)General-Purpose Computation on GPUs in the Browser Using gpu.jsComputing in Science and Engineering10.1109/MCSE.2018.10816311620:1(33-42)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1109/MCSE.2018.108163116
SuB TDoring NBrinkmann ANagel L(2018)And Now for Something Completely Different: Running Lisp on GPUs2018 IEEE International Conference on Cluster Computing (CLUSTER)10.1109/CLUSTER.2018.00060(434-444)Online publication date: Sep-2018
https://doi.org/10.1109/CLUSTER.2018.00060
Benmerar TKachouane MOulebsir-Boumghar FDeriche R(2014)A Hybrid SaaS/Grid Architecture for Diffusion MRI in Brain Imaging FieldInternational Journal of Organizational and Collective Intelligence10.4018/ijoci.20141001024:4(24-58)Online publication date: 1-Oct-2014
https://dl.acm.org/doi/10.4018/ijoci.2014100102

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