COBRRA: COntention aware cache Bypass with Request-Response Arbitration

IF 2.8 3区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE ACM Transactions on Embedded Computing Systems Pub Date : 2023-11-17 DOI:10.1145/3632748
Aritra Bagchi, Dinesh Joshi, Preeti Ranjan Panda
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Abstract

In modern multi-processor systems-on-chip (MPSoCs), requests from different processor cores, accelerators, and their responses from the lower level memory contend for the shared cache bandwidth, making it a critical performance bottleneck. Prior research on shared cache management has considered requests from cores, but has ignored crucial contributions from their responses. Prior cache bypass techniques focused on data reuse and neglected the system-level implications of shared cache contention. We propose COBRRA, a novel shared cache controller policy that mitigates the contention by aggressively bypassing selected responses from the lower level memory, and scheduling the remaining requests and responses to the cache efficiently. COBRRA is able to improve the average performance of a set of 15 SPEC workloads by \(49\% \) and \(33\% \) compared to the no-bypass baseline and the best performing state-of-the-art bypass solution, respectively. Furthermore, COBRRA reduces the overall cache energy consumption by \(38\% \) and \(31\% \) compared to the no-bypass baseline and the most energy-efficient state-of-the-art bypass solution, respectively.

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具有请求-响应仲裁的争用感知缓存旁路
在现代的多处理器片上系统(mpsoc)中,来自不同处理器内核、加速器的请求及其来自底层内存的响应会争夺共享缓存带宽,从而成为关键的性能瓶颈。先前关于共享缓存管理的研究考虑了来自核心的请求,但忽略了它们的响应的关键贡献。先前的缓存绕过技术侧重于数据重用,而忽略了共享缓存争用的系统级含义。我们提出了一种新的共享缓存控制器策略COBRRA,它通过积极地绕过来自底层内存的选定响应,并有效地将剩余的请求和响应调度到缓存中,从而减轻了争用。与无旁路基线和性能最佳的最先进旁路解决方案相比,COBRRA能够将一组15个SPEC工作负载的平均性能分别提高\(49\% \)和\(33\% \)。此外,与无旁路基线和最节能的最先进的旁路解决方案相比,COBRRA将总体缓存能耗分别降低\(38\% \)和\(31\% \)。
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来源期刊
ACM Transactions on Embedded Computing Systems
ACM Transactions on Embedded Computing Systems 工程技术-计算机:软件工程
CiteScore
3.70
自引率
0.00%
发文量
138
审稿时长
6 months
期刊介绍: The design of embedded computing systems, both the software and hardware, increasingly relies on sophisticated algorithms, analytical models, and methodologies. ACM Transactions on Embedded Computing Systems (TECS) aims to present the leading work relating to the analysis, design, behavior, and experience with embedded computing systems.
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