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Exploiting commutativity to reduce the cost of updates to shared data in cache-coherent systems

机译:利用可交换性来降低缓存一致性系统中共享数据更新的成本

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摘要

We present Coup, a technique to lower the cost of updates to shared data in cache-coherent systems. Coup exploits the insight that many update operations, such as additions and bitwise logical operations, are commutative: they produce the same final result regardless of the order they are performed in. Coup allows multiple private caches to simultaneously hold update-only permission to the same cache line. Caches with update-only permission can locally buffer and coalesce updates to the line, but cannot satisfy read requests. Upon a read request, Coup reduces the partial updates buffered in private caches to produce the final value. Coup integrates seamlessly into existing coherence protocols, requires inexpensive hardware, and does not affect the memory consistency model.We apply Coup to speed up single-word updates to shared data. On a simulated 128-core, 8-socket system, Coup accelerates state-of-the-art implementations of update-heavy algorithms by up to 2.4×.
机译:我们提出了Coup,一种降低缓存一致性系统中共享数据更新成本的技术。 Coup利用了很多更新操作(例如加法和按位逻辑操作)是可交换的见解:无论执行顺序如何,它们都会产生相同的最终结果。Coup允许多个专用缓存同时对同一对象持有仅更新权限快取线。具有仅更新权限的缓存可以在本地缓冲和合并对行的更新,但不能满足读取请求。根据读取请求,Coup会减少专用缓存中缓冲的部分更新,以产生最终值。 Coup无缝集成到现有的一致性协议中,需要廉价的硬件,并且不影响内存一致性模型。我们应用Coup来加快对共享数据的单字更新。在模拟的128核,8插槽系统上,Coup可以将最新的繁重算法的实现加速多达2.4倍。

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