Accurate Fork-Join Profiling on the Java Virtual Machine
Authors: 
Matteo Basso, Eduardo Rosales, Filippo Schiavio, Andrea Rosà, Walter BinderAuthors Info & Claims
Matteo Basso, Eduardo Rosales, Filippo Schiavio, Andrea Rosà, Walter BinderAuthors Info & ClaimsPages 35 - 50
Abstract
The fork-join model for parallel computing has become very popular and is included in the Java class library since Java 7. While understanding and optimizing the performance of fork-join computations is of paramount importance, accurately profiling them on the Java Virtual Machine (JVM) is challenging due to the complexity of the API. In this paper, we present a novel model for analyzing fork-join computations on the JVM, addressing the peculiarities of the Java fork-join framework, including features such as task unforking and task reuse. We implement our model in a profiler that detects every spawned fork-join task, capturing all task dependencies and aiming at collecting cycle-accurate task-granularity data. We evaluate our profiler against a dedicated fork-join profiler for the JVM, showing that our tool achieves higher profile accuracy and introduces less overhead.
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© Springer Nature Switzerland AG 2022.
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Springer-Verlag
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Published: 22 August 2022
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