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A Hardware Approach to Fairly Balance the Inter-Thread Interference in Shared Caches

机译：公平地平衡共享缓存中线程间干扰的硬件方法

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Shared caches have become the common design choice in the vast majority of modern multi-core and many-core processors, since cache sharing improves throughput for a given silicon area. Sharing the cache, however, has a downside: the requests from multiple applications compete among them for cache resources, so the execution time of each application increases over isolated execution. The degree in which the performance of each application is affected by the interference becomes unpredictable yielding the system to unfairness situations. This paper proposes Fair-Progress Cache Partitioning (FPCP), a low-overhead hardware-based cache partitioning approach that addresses system fairness. FPCP reduces the interference by allocating to each application a cache partition and adjusting the partition sizes at runtime. To adjust partitions, our approach estimates during multicore execution the time each application would have taken in isolation, which is challenging. The proposed approach has two main differences over existing approaches. First, FPCP distributes cache ways incrementally, which makes the proposal less prone to estimation errors. Second, the proposed algorithm is much less costly than the state-of-the-art ASM-Cache approach. Experimental results show that, compared to ASM-Cache, FPCP reduces unfairness by 48 percent in four-application workloads and by 28 percent in eight-application workloads, without harming the performance.
机译：共享缓存已成为绝大多数现代多核和多核处理器中常见的设计选择，因为缓存共享可提高给定硅面积的吞吐量。但是，共享缓存有一个缺点：多个应用程序的请求在它们之间争用缓存资源，因此，每个应用程序的执行时间会比孤立执行的时间更长。每个应用程序的性能受干扰影响的程度变得不可预测，从而使系统陷入不公平状况。本文提出了公平进程缓存分区（FPCP），这是一种基于硬件的低开销的缓存分区方法，可解决系统公平性问题。 FPCP通过为每个应用程序分配一个缓存分区并在运行时调整分区大小来减少干扰。为了调整分区，我们的方法估计了在多核执行期间每个应用程序将被单独占用的时间，这具有挑战性。提议的方法与现有方法有两个主要区别。首先，FPCP增量地分配缓存方式，这使提案不太容易出现估计错误。其次，所提出的算法比最新的ASM缓存方法要便宜得多。实验结果表明，与ASM缓存相比，FPCP在不损害性能的情况下将四个应用程序工作负载的不公平性降低了48％，将八个应用程序工作负载的不公平性降低了28％。

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