Workload characterization of server-side JavaScript

Recently, scripting languages are becoming popular as languages to develop server-side applications. Modern JavaScript compilers significantly optimize JavaScript code, but their main targets are client-side Web applications. In this paper, we characterize the runtime behaviors of server workloads o...

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Vydáno v:2014 IEEE International Symposium on Workload Characterization (IISWC) s. 13 - 21
Hlavní autor: Ogasawara, Takeshi
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.10.2014
Témata:
Benchmark testing
Electric breakdown
Engines
Libraries
Runtime
Servers
ISBN:9781479964529, 1479964522
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Shrnutí:Recently, scripting languages are becoming popular as languages to develop server-side applications. Modern JavaScript compilers significantly optimize JavaScript code, but their main targets are client-side Web applications. In this paper, we characterize the runtime behaviors of server workloads on an emerging JavaScript server-side framework, Node.js, comparing it to client-side JavaScript code. The runtime profile shows that a large amount (47.5% on average) of the total CPU time is spent in the V8 C++ library used for server workloads, while only 3.2% is for client-side programs. Such high CPU usage in the C++ code limits the performance improvements for server workloads, since recent changes in the performance of client-side workloads are due to optimized JavaScript code. Our analysis of complex calling contexts reveals that function calls to the V8 runtime from the server-side framework to handle JavaScript objects significantly contribute to the high CPU usage in the V8 library (up to 22.5% of the total time and 15.4% on average). We also show that the function calls to the V8 runtime from compiled JavaScript code are another source of the high CPU usage in the V8 library code (up to 24.5% of the total and 18.7% on average). Only a few JavaScript functions that implement the server-side framework API make these function calls to the V8 runtime and contribute to a large amount of the CPU time (up to 6.8% of the total).
ISBN:9781479964529
1479964522
DOI:10.1109/IISWC.2014.6983035