NDLI: Statistically rigorous java performance evaluation

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Statistically rigorous java performance evaluation

Content Provider	ACM Digital Library
Author	Georges, Andy Eeckhout, Lieven Buytaert, Dries
Abstract	Java performance is far from being trivial to benchmark because it is affected by various factors such as the Java application, its input, the virtual machine, the garbage collector, the heap size, etc. In addition, non-determinism at run-time causes the execution time of a Java program to differ from run to run. There are a number of sources of non-determinism such as Just-In-Time (JIT) compilation and optimization in the virtual machine (VM) driven by timer-based method sampling, thread scheduling, garbage collection, and various. There exist a wide variety of Java performance evaluation methodologies usedby researchers and benchmarkers. These methodologies differ from each other in a number of ways. Some report average performance over a number of runs of the same experiment; others report the best or second best performance observed; yet others report the worst. Some iterate the benchmark multiple times within a single VM invocation; others consider multiple VM invocations and iterate a single benchmark execution; yet others consider multiple VM invocations and iterate the benchmark multiple times. This paper shows that prevalent methodologies can be misleading, and can even lead to incorrect conclusions. The reason is that the data analysis is not statistically rigorous. In this paper, we present a survey of existing Java performance evaluation methodologies and discuss the importance of statistically rigorous data analysis for dealing with non-determinism. We advocate approaches to quantify startup as well as steady-state performance, and, in addition, we provide the JavaStats software to automatically obtain performance numbers in a rigorous manner. Although this paper focuses on Java performance evaluation, many of the issues addressed in this paper also apply to other programming languages and systems that build on a managed runtime system.
Starting Page	57
Ending Page	76
Page Count	20
File Format	PDF
ISBN	9781595937865
DOI	10.1145/1297027.1297033
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-10-21
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Java Data analysis Methodology Benchmarking Statistics
Content Type	Text
Resource Type	Article

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