River trail: a path to parallelism in JavaScript
Proceedings of the 2013 ACM SIGPLAN international conference on Object oriented programming systems languages & applications
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Today, more than 99% of web-browsers are enabled with Javascript capabilities, and Javascript's popularity is only going to increase in the future. However, due to bytecode interpretation, Javascript codes suffer from severe performance penalty (up to 50x slower) compared to the corresponding native C/C++ code. We recognize that the first step to bridge this performance gap is to understand the the architectural execution characteristics of Javascript benchmarks. Therefore, this paper presents an in-depth architectural characterization of widely used V8 and Sunspider Javascript benchmarks using Google's V8 javascript engine. Using statistical data analysis techniques, our characterization study discovers and explains correlation among different execution characteristics in microarchitecture dependent as well as microarchitecture independent fashion. Furthermore, our study measures (dis)similarity among 33 different Javascript benchmarks and discusses its implications. Given the widespread use of Javascripts, we believe our findings are useful for both performance analysis and benchmarking communities.