用MCTOP抽象多核拓扑

Georgios Chatzopoulos, R. Guerraoui, T. Harris, Vasileios Trigonakis
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引用次数: 12

摘要

在多核计算中,可移植性和效率通常是对立的。为了开发高效的代码,需要考虑目标多核的拓扑结构(例如,局部性)。这显然阻碍了代码的可移植性。在本文中,我们证明了鱼与熊掌兼得。我们介绍MCTOP,一个多核拓扑的抽象,增加了重要的底层硬件信息,如内存带宽和通信延迟。我们展示了如何使用libmctop自动生成MCTOP, libmctop是我们的库,它利用缓存一致性协议的确定性,仅使用延迟测量来推断多核的拓扑结构。MCTOP使开发人员能够准确地、可移植地定义高级性能优化策略。我们通过四个例子说明了几个这样的策略:(i-ii)在OpenMP和MapReduce库中的线程放置,(iii)拓扑感知合并排序算法,以及(iv)锁的自动回退方案。我们演示了这些优化在来自Intel、AMD和Oracle的五种处理器上的可移植性,而且不费力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Abstracting Multi-Core Topologies with MCTOP
Portability and efficiency are usually antagonists in multi-core computing. In order to develop efficient code, one needs to take into account the topology of the target multi-cores (e.g., for locality). This clearly hampers code portability. In this paper, we show that you can have the cake and eat it too. We introduce MCTOP, an abstraction of multi-core topologies augmented with important low-level hardware information, such as memory bandwidths and communication latencies. We show how to automatically generate MCTOP using libmctop, our library that leverages the determinism of cache-coherence protocols to infer the topology of multi-cores using only latency measurements. MCTOP enables developers to accurately and portably define high-level performance optimization policies. We illustrate several such policies through four examples: (i-ii) thread placement in OpenMP and in a MapReduce library, (iii) a topology-aware mergesort algorithm, as well as (iv) automatic backoff schemes for locks. We illustrate the portability of these optimizations on five processors from Intel, AMD, and Oracle, with low effort.
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