NDLI: An Efficient and Generic Event-based Profiler Framework for Dynamic Languages

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An Efficient and Generic Event-based Profiler Framework for Dynamic Languages

Content Provider	ACM Digital Library
Author	Larsen, Per Van de Vanter, Michael L. Brunthaler, Stefan Franz, Michael Savrun-Yeniçeri, Gülfem
Abstract	Profilers help programmers analyze their programs and identify performance bottlenecks. We implement a profiler framework that helps to compare and analyze programs implementing the same algorithms written in different languages. Profiler implementers replicate common functionalities in their language profilers. We focus on building a generic profiler framework for dynamic languages to minimize the recurring implementation effort. We implement our profiler in a framework that optimizes abstract syntax tree (AST) interpreters using a just-in-time (JIT) compiler. We evaluate it on ZipPy and JRuby+Truffle, Python and Ruby implementations in this framework, respectively. We show that our profiler runs faster than the existing profilers in these languages and requires modest implementation effort. Our profiler serves three purposes: 1) helps users to find the bottlenecks in their programs, 2) helps language implementers to improve the performance of their language implementation, 3) helps to compare and evaluate different languages on cross-language benchmarks.
Starting Page	102
Ending Page	112
Page Count	11
File Format	PDF
ISBN	9781450337120
DOI	10.1145/2807426.2807435
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-09-08
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Profiling Abstract syntax tree interpreters Pypy Java virtual machine Jruby Ruby Dynamic languages Python
Content Type	Text
Resource Type	Article

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