NDLI: Fast Java profiling with scheduling-aware stack fragment sampling and asynchronous analysis

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Fast Java profiling with scheduling-aware stack fragment sampling and asynchronous analysis

Content Provider	ACM Digital Library
Author	Hofer, Peter Mössenböck, Hanspeter
Abstract	Sampling is a popular approach to profiling because it typically has only a small impact on performance and does not modify the profiled application. Common sampling profilers collect data about an application by pausing the application threads, walking the stacks to create stack traces, and then adding the traces to their profile. Waiting threads are often sampled as well, even when they have not been active since their last sample. Sampling profilers for Java commonly rely on safepoints, which are locations in the Java code where a thread can pause to be sampled. However, restricting profiling to these locations affects the accuracy of the profile, and the safepoint mechanism itself imposes significant pause times on the application. We present stack fragment sampling, a new approach for Java applications that minimizes pause times and eliminates redundant samples altogether. It interrupts an application thread only to copy a fragment of its stack to a buffer and then immediately resumes its execution. Retrieving and decoding the stack fragments happens asynchronously and can run on a separate core or on another processor. Our approach integrates with the operating system to only take samples of threads while they are running in order to avoid redundant samples. We demonstrate that our approach has a very small impact on performance even at high sampling rates. Furthermore, we validate our approach by comparing our profiles to those from a profiler using safepoints as well as to a VM-internal profiler that does not use safepoints. The results show that the profiles agree.
Starting Page	145
Ending Page	156
Page Count	12
File Format	PDF
ISBN	9781450329262
DOI	10.1145/2647508.2647509
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-09-23
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Java Calling context Profiling Sampling Monitoring
Content Type	Text
Resource Type	Article

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