A limit study of JavaScript parallelism

Authors:
Emily Fortuna;Owen Anderson;Luis Ceze;Susan Eggers
Affiliations:
Computer Science and Engineering, University of Washington, USA;Computer Science and Engineering, University of Washington, USA;Computer Science and Engineering, University of Washington, USA;Computer Science and Engineering, University of Washington, USA
Venue:
IISWC '10 Proceedings of the IEEE International Symposium on Workload Characterization (IISWC'10)
Year:
2010

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Abstract

JavaScript is ubiquitous on the web. At the same time, the language's dynamic behavior makes optimizations challenging, leading to poor performance. In this paper we conduct a limit study on the potential parallelism of JavaScript applications, including popular web pages and standard JavaScript benchmarks. We examine dependency types and looping behavior to better understand the potential for JavaScript parallelization. Our results show that the potential speedup is very encouraging— averaging 8.9x and as high as 45.5x. Parallelizing functions themselves, rather than just loop bodies proves to be more fruitful in increasing JavaScript execution speed. The results also indicate in our JavaScript engine, most of the dependencies manifest via virtual registers rather than hash table lookups.