Minimal disturbance placement and promotion

Elvira Teran, Yingying Tian, Zhe Wang, Daniel A. Jiménez
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引用次数: 13

Abstract

Cache replacement policies often order blocks into distinct positions. A block is placed into a set in some initial position. A re-referenced block is promoted into a higher position while other blocks may move into lower positions. A block in the lowest position is a candidate for replacement. Tree-based PseudoLRU is a well-known space-efficient replacement policy based on representing block positions as distinct paths in a binary tree. We find that a placement or promotion for one block often needlessly disturbs the non-promoted blocks. Guided by the principle of minimal disturbance, i.e. that a policy should seek to disturb the order of non-promoted blocks to the smallest extent possible, we develop a simple modification to PseudoLRU resulting in a policy that improves performance over previous techniques while retaining the low cost of PseudoLRU. The result is a minimal disturbance placement and promotion (MDPP) policy. We first give a static formulation of MDPP and show that it provides superior performance to LRU, PseudoLRU and matches performance for SRRIP for both single-threaded and multi-core workloads. We then give a dynamic formulation that uses dead block prediction for placement and bypass and show that it meets or exceeds state-of-the-art performance with lower overhead. For single-threaded workloads, dynamic MDPP matches the 5.9% speedup over LRU of the state-of-the-art policy SHiP. For multi-core workloads, dynamic MDPP gives a normalized weighted speedup of 14.3% over LRU, compared with SHiP that yields a speedup of 12.3% over LRU and requires double the storage overhead per set. We show that minimal disturbance policies can reduce the frequency of a costly read-modify-write cycle for replacement state, making them potentially suitable for future work in DRAM caches.
最小干扰放置和提升
缓存替换策略通常将块排序到不同的位置。将块放在集合的某个初始位置。重新引用的块被提升到较高的位置,而其他块可能会移动到较低的位置。最低位置的块是替换的候选块。基于树的伪olru是一种众所周知的空间高效替换策略,它基于将块位置表示为二叉树中的不同路径。我们发现,一个块的放置或提升通常会不必要地干扰未提升的块。在最小干扰原则的指导下,即策略应该寻求在尽可能小的程度上干扰非提升块的顺序,我们开发了对pseudo - olru的简单修改,从而使策略比以前的技术提高了性能,同时保留了pseudo - olru的低成本。结果是一个最小干扰放置和提升(MDPP)政策。我们首先给出了MDPP的静态公式,并表明它在单线程和多核工作负载下提供了优于LRU, PseudoLRU和SRRIP的性能。然后,我们给出了一个动态公式,该公式使用死块预测来放置和绕过,并表明它以更低的开销达到或超过最先进的性能。对于单线程工作负载,动态MDPP与最先进策略SHiP的LRU相比有5.9%的加速。对于多核工作负载,动态MDPP比LRU提供了14.3%的标准化加权加速,而SHiP比LRU提供了12.3%的加速,并且需要两倍的存储开销。我们表明,最小干扰策略可以减少替换状态的昂贵的读-修改-写周期的频率,使它们可能适用于DRAM缓存的未来工作。
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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