Accelerating and Adapting Precomputation Threads for Effcient Prefetching

Weifeng Zhang, D. Tullsen, B. Calder
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引用次数: 71

Abstract

Speculative precomputation enables effective cache prefetching for even irregular memory access behavior, by using an alternate thread on a multithreaded or multi-core architecture. This paper describes a system that constructs and runs precomputation based prefetching threads via event-driven dynamic optimization. Precomputation threads are dynamically constructed by a runtime compiler from the program's frequently executed hot traces, and are adapted to the memory behavior automatically. Both construction and execution of the prefetching threads happen in another thread, imposing little overhead on the main thread. This paper also presents several techniques to accelerate the precomputation threads, including colocation of p-threads with hot traces, dynamic stride prediction, and automatic adaptation of runahead and jumpstart distance. The adaptive prefetching achieves 42% speedup, a 17% improvement over existing p-thread prefetching schemes
加速和调整预计算线程以实现高效预取
通过在多线程或多核架构上使用备用线程,推测性预计算可以对不规则的内存访问行为进行有效的缓存预取。本文描述了一个基于事件驱动动态优化的预取线程构建和运行预计算的系统。预计算线程由运行时编译器根据程序频繁执行的热跟踪动态构造,并自动适应内存行为。预取线程的构造和执行都发生在另一个线程中,对主线程的开销很小。本文还提出了几种加速预计算线程的技术,包括带热迹的p线程的并发、动态步幅预测和自动适应跑前和跳起距离。自适应预取实现了42%的加速,比现有的p线程预取方案提高了17%
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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