2017 24th Asia-Pacific Software Engineering Conference (APSEC) (2017)
Nanjing, Jiangsu, China
Dec. 4, 2017 to Dec. 8, 2017
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/APSEC.2017.67
The analysis of task granularity in parallel applications (i.e., the amount of work to be performed by parallel tasks) is essential to unveil performance problems and to optimize task-parallel applications. Too small task granularities may result in high parallelization overheads, while too large task granularities may indicate missed parallelization opportunities. Despite the importance of task granularity, this metric is not considered by existing profilers for parallel applications on the Java Virtual Machine (JVM). In this paper we present tgp, a novel task-granularity profiler for multi-threaded applications on the JVM. tgp collects bytecode- and hardware-level metrics to characterize task granularity, assisting the developer in diagnosing and locating parallelization shortcomings.
Java, multi-threading, virtual machines
E. Rosales, A. Rosa and W. Binder, "tgp: A Task-Granularity Profiler for the Java Virtual Machine," 2017 24th Asia-Pacific Software Engineering Conference (APSEC), Nanjing, Jiangsu, China, 2018, pp. 570-575.