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Fast thread migration via cache working set prediction

机译:通过缓存工作集预测进行快速线程迁移

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The most significant source of lost performance when a thread migrates between cores is the loss of cache state. A significant boost in post-migration performance is possible if the cache working set can be moved, proactively, with the thread. This work accelerates thread startup performance after migration by predicting and prefetching the working set of the application into the new cache. It shows that simply moving cache state performs poorly, and that moving the instruction working set can be even more critical than data. This paper demonstrates a technique that captures the access behavior of a thread, summarizes that behavior into a compact form for transfer between cores, and then prefetches appropriate data into the new caches based on the summary. It presents a detailed study of single-thread migration effects, and then demonstrates its utility on a speculative multithreading architecture. Working set prediction as much as doubles the performance of short-lived threads, and in a full speculative multithreading implementation, the technique is also shown to nearly double the effectiveness of the spawned threads.
机译:当线程在内核之间迁移时,性能损失的最主要来源是高速缓存状态的丢失。如果可以通过线程主动移动缓存工作集,则可以大大提高迁移后的性能。通过预测和预取应用程序的工作集到新的缓存中,这项工作可以在迁移后提高线程启动性能。它表明,仅移动高速缓存状态的性能较差,并且移动指令工作集可能比数据更为关键。本文演示了一种技术,该技术可捕获线程的访问行为,将该行为汇总为紧凑形式以在内核之间传输,然后根据摘要将适当的数据预取到新的高速缓存中。它提供了对单线程迁移效果的详细研究,然后展示了其在推测性多线程体系结构上的效用。工作集预测可使短寿命线程的性能提高一倍,并且在完全推测性的多线程实现中,该技术还显示出将产生的线程的效率提高近一倍。

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