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Kismet: Parallel Speedup Estimates for Serial Programs

机译:Kismet:串行程序的并行加速估计

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摘要

Software engineers now face the difficult task of refactoring serial programs for parallel execution on multicore processors. Currently, they are offered little guidance as to how much benefit may come from this task, or how close they are to the best possible parallelization. This paper presents Kismet, a tool that creates parallel speedup estimates for unparallelized serial programs. Kismet differs from previous approaches in that it does not require any manual analysis or modification of the program. This difference allows quick analysis of many programs, avoiding wasted engineering effort on those that are fundamentally limited. To accomplish this task, Kismet builds upon the hierarchical critical path analysis (HCPA) technique, a recently developed dynamic analysis that localizes parallelism to each of the potentially nested regions in the target program. It then uses a parallel execution time model to compute an approximate upper bound for performance, modeling constraints that stem from both hardware parameters and internal program structure. Our evaluation applies Kismet to eight high-parallelism NAS Parallel Benchmarks running on a 32-core AMD multicore system, five low-parallelism Speclnt benchmarks, and six medium-parallelism benchmarks running on the finegrained MIT Raw processor. The results are compelling. Kismet is able to significantly improve the accuracy of parallel speedup estimates relative to prior work based on critical path analysis.
机译:现在,软件工程师面临着重构串行程序以在多核处理器上并行执行的艰巨任务。当前,对于这些任务可能带来多少收益或它们与最佳并行化的距离有多远,他们几乎没有提供指导。本文介绍了Kismet,该工具可为无并行串行程序创建并行加速估算。 Kismet与以前的方法不同之处在于,它不需要任何手动分析或修改程序。这种差异允许对许多程序进行快速分析,从而避免了从根本上限制程序的工程量。为了完成此任务,Kismet建立在分层关键路径分析(HCPA)技术的基础上,该技术是最近开发的一种动态分析,该分析将并行性定位到目标程序中每个可能嵌套的区域。然后,它使用并行执行时间模型来计算性能的近似上限,对源自硬件参数和内部程序结构的约束进行建模。我们的评估将Kismet应用于运行在32核AMD多核系统上的八个高并行度NAS并行基准测试,五个运行在细粒度的MIT Raw处理器上的低并行度Speclnt基准测试和六个中等并行度基准测试。结果令人信服。与基于关键路径分析的先前工作相比,Kismet能够显着提高并行加速估计的准确性。

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