ParallelJS: An Execution Framework for JavaScript on Heterogeneous Systems

Authors:
Jin Wang;Norman Rubin;Sudhakar Yalamanchili
Affiliations:
Georgia Institute of Technology Atlanta, 30332;NVIDIA Research California, 95050;Georgia Institute of Technology Atlanta, 30332
Venue:
Proceedings of Workshop on General Purpose Processing Using GPUs
Year:
2014

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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.