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LFOC+: A Fair OS-Level Cache-Clustering Policy for Commodity Multicore Systems

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2022

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IEEE
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J. C. Saez, F. Castro, G. Fanizzi and M. Prieto-Matias, "LFOC+: A Fair OS-Level Cache-Clustering Policy for Commodity Multicore Systems," in IEEE Transactions on Computers, vol. 71, no. 8, pp. 1952-1967, 1 Aug. 2022, doi: 10.1109/TC.2021.3112970

Abstract

Commodity multicore systems are increasingly adopting hardware support that enables the system software to partition the last-level cache (LLC). This support makes it possible for the operating system (OS) or the Virtual Machine Monitor (VMM) to mitigate shared-resource contention effects on multicores by assigning different co-running applications to various cache partitions. Recently cache-clustering (or partition-sharing) strategies have emerged as a way to improve system throughput and fairness on new platforms with cache-partitioning support. As opposed to strict cache-partitioning, which allocates separate cache partitions to each application, cache-clustering allows partitions to be shared by a group of applications. In this article we propose LFOC+, a fairness-aware OS-level cache-clustering policy for commodity multicore systems. LFOC+ tries to mimic the behavior of the optimal cache-clustering solution for fairness, which we could obtain for different workload scenarios by using a simulation tool. Our dynamic cache-clustering strategy continuously gathers data fromperformancemonitoring counters to classify applications at runtime based on the degree of cache sensitivity and contentiousness, and effectively separates cache-sensitive applications fromaggressor programs to improve fairness,while providing acceptable system throughput.We implemented LFOC+ in the Linux kernel and evaluated it on a real systemfeaturing an Intel Skylake processor, wherewe compare its effectiveness to that of four previously proposed cache-clustering policies. Our experimental análisis reveals that LFOC+ constitutes a lightweight OS-level policy and improves fairness relative to two other state-of-the-art fairness-aware strategies –Dunn and LFOC–, by up to 22% and up to 20.6%, respectively, and by9% and 4.9%on average.

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