Compute Caches

Shaizeen Aga, Supreet Jeloka, Arun K. Subramaniyan, S. Narayanasamy, D. Blaauw, R. Das
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引用次数: 241

Abstract

This paper presents the Compute Cache architecturethat enables in-place computation in caches. ComputeCaches uses emerging bit-line SRAM circuit technology to repurpose existing cache elements and transforms them into active very large vector computational units. Also, it significantlyreduces the overheads in moving data between different levelsin the cache hierarchy. Solutions to satisfy new constraints imposed by ComputeCaches such as operand locality are discussed. Also discussedare simple solutions to problems in integrating them into aconventional cache hierarchy while preserving properties suchas coherence, consistency, and reliability. Compute Caches increase performance by 1.9× and reduceenergy by 2.4× for a suite of data-centric applications, includingtext and database query processing, cryptographic kernels, and in-memory checkpointing. Applications with larger fractionof Compute Cache operations could benefit even more, asour micro-benchmarks indicate (54× throughput, 9× dynamicenergy savings).
计算缓存
本文提出了一种能够在缓存中进行就地计算的计算缓存体系结构。ComputeCaches使用新兴的位线SRAM电路技术来重新利用现有的缓存元素,并将它们转换为活动的超大矢量计算单元。此外,它还显著减少了在缓存层次结构的不同级别之间移动数据的开销。讨论了满足ComputeCaches施加的新约束(如操作数局部性)的解决方案。还讨论了将它们集成到传统缓存层次结构中同时保留一致性、一致性和可靠性等属性的简单解决方案。对于一套以数据为中心的应用程序(包括文本和数据库查询处理、加密内核和内存中的检查点),计算缓存的性能提高了1.9倍,能耗降低了2.4倍。具有较大部分计算缓存操作的应用程序可能会受益更多,正如我们的微基准测试所表明的那样(54倍吞吐量,9倍动态节能)。
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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