ParallelJS: An Execution Framework for JavaScript on Heterogeneous Systems
Jin Wang, Norman Rubin and Sudhakar Yalamanchili. “ParallelJS: An Execution Framework for JavaScript on Heterogeneous Systems.” Seventh Workshop on General Purpose Processing Using GPUs (GPGPU-7). March, 2014.
Abstract
JavaScript has been recognized as one of the most widely used script languages. Optimizations of JavaScript engines on mainstream web browsers enable ecient 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 exible 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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Citation
@inproceedings{wang-gpgpu7-paralleljs,
author={Jin Wang, Norman Rubin and Sudhakar Yalamanchili},
booktitle={Seventh Workshop on General Purpose Processing Using GPUs (GPGPU-7)},
title={ParallelJS: An Execution Framework for JavaScript on Heterogeneous Systems},
year={2014},
month={March},
}
author={Jin Wang, Norman Rubin and Sudhakar Yalamanchili},
booktitle={Seventh Workshop on General Purpose Processing Using GPUs (GPGPU-7)},
title={ParallelJS: An Execution Framework for JavaScript on Heterogeneous Systems},
year={2014},
month={March},
}
