科研之友
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摘要
The performance of parallel code significantly depends on the parallel task granularity (PTG). If the PTG is too coarse, performance suffers due to load imbalance; if the PTG is too fine, performance suffers from the overhead that is induced by parallel task creation and scheduling. This paper presents a software platform that automatically determines the PTG at run-time. Automatic PTG selection is enabled by concurrent calls, which are special source language constructs that provide a late decision (at run-time) of whether concurrent calls are executed sequentially or concurrently (as a parallel task). Furthermore, the execution semantics of concurrent calls permits the runtime system to merge two (or more) concurrent calls thereby coarsening the PTG. We present an integration of concurrent calls into the Java programming language, the Java Memory Model, and show how the Java Virtual Machine can adapt the PTG based on dynamic profiling. The performance evaluation shows that our runtime system performs competitively to Java programs for which the PTG is tuned manually. Compared to an unfortunate choice of the PTG, this approach performs up to 3x faster than standard Java code.
- 出版日期2013-10
