Mohamed M. Saad, R. Palmieri, B. Ravindran
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引用次数: 1

摘要

我们提出了Lerna,一个端到端工具,自动和透明地检测和提取数据依赖顺序循环的并行性。Lerna将推测与一系列技术相结合,包括代码分析、依赖分析、检测和自适应执行。为了避免保守的行动和发现实际的冲突,需要进行推测。Lerna针对的是由于数据依赖而难以并行化的应用程序。我们的实验研究涉及13个具有数据依赖性的应用程序的并行化。在24核机器上的结果显示,微基准测试的平均加速为2.7倍,宏观基准测试的平均加速为2.5倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lerna
We present Lerna, an end-to-end tool that automatically and transparently detects and extracts parallelism from data-dependent sequential loops. Lerna uses speculation combined with a set of techniques including code profiling, dependency analysis, instrumentation, and adaptive execution. Speculation is needed to avoid conservative actions and detect actual conflicts. Lerna targets applications that are hard-to-parallelize due to data dependency. Our experimental study involves the parallelization of 13 applications with data dependencies. Results on a 24-core machine show an average of 2.7× speedup for micro-benchmarks and 2.5× for the macro-benchmarks.
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