Base-Victim Compression: An Opportunistic Cache Compression Architecture

Jayesh Gaur, Alaa R. Alameldeen, S. Subramoney
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引用次数: 25

Abstract

The memory wall has motivated many enhancements to cache management policies aimed at reducing misses. Cache compression has been proposed to increase effective cache capacity, which potentially reduces capacity and conflict misses. However, complexity in cache compression implementations could increase cache power and access latency. On the other hand, advanced cache replacement mechanisms use heuristics to reduce misses, leading to significant performance gains. Both cache compression and replacement policies should collaborate to improve performance. In this paper, we demonstrate that cache compression and replacement policies can interact negatively. In many workloads, performance gains from replacement policies are lost due to the need to alter the replacement policy to accommodate compression. This leads to sub-optimal replacement policies that could lose performance compared to an uncompressed cache. We introduce a novel, opportunistic cache compression mechanism, Base-Victim, based on an efficient cache design. Our compression architecture improves performance on top of advanced cache replacement policies, and guarantees a hit rate at least as high as that of an uncompressed cache. For cache-sensitive applications, Base-Victim achieves an average 7.3% performance gain for single-threaded workloads, and 8.7% gain for four-thread multi-program workload mixes.
基础受害者压缩:一个机会缓存压缩架构
内存墙激发了对缓存管理策略的许多增强,旨在减少失误。缓存压缩被提出用于增加有效的缓存容量,从而潜在地减少容量和冲突缺失。然而,缓存压缩实现的复杂性可能会增加缓存能力和访问延迟。另一方面,高级缓存替换机制使用启发式方法来减少失误,从而显著提高性能。缓存压缩和替换策略应该协作以提高性能。在本文中,我们证明了缓存压缩和替换策略可以负交互。在许多工作负载中,由于需要更改替换策略以适应压缩,从替换策略中获得的性能收益会丢失。这将导致次优替换策略,与未压缩缓存相比,可能会损失性能。我们介绍了一种基于高效缓存设计的新型机会缓存压缩机制——Base-Victim。我们的压缩架构在高级缓存替换策略的基础上提高了性能,并保证命中率至少与未压缩缓存一样高。对于缓存敏感的应用程序,Base-Victim在单线程工作负载下的平均性能提升为7.3%,在四线程多程序工作负载混合下的平均性能提升为8.7%。
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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