CARE: A Concurrency-Aware Enhanced Lightweight Cache Management Framework
CARE: A Concurrency-Aware Enhanced Lightweight Cache Management Framework
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DOI：
10.1109/hpca56546.2023.10071125
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发表时间：
2023-02
期刊：
影响因子：
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通讯作者：
Xiaoyang Lu;Rujia Wang;Xian-He Sun
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文献类型：
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作者：
Xiaoyang Lu;Rujia Wang;Xian-He Sun
提高缓存性能是一个持久的研究课题。在利用数据局部性提高缓存性能变得越来越困难的同时，数据访问并发性为缓存性能优化提供了新的机会。在这项工作中，我们提出了一种新的并发感知缓存管理框架，优于最先进的本地缓存管理计划。首先，我们调查的数据访问并发性的优点，并指出，降低未命中率可能不一定会导致更好的整体性能。接下来，我们引入了纯未命中贡献（PMC）指标，一个轻量级的和通用的并发感知指标，通过考虑数据并发性来准确地测量每个未命中访问的成本。然后，我们提出了照顾，一个动态可调的，并发意识，低开销的高速缓存管理框架的帮助下，PMC指标。我们在不同的应用领域进行了广泛的实验，评估了CARE，并考虑了数据并发性，显示出显着的性能提升。在4核系统中，CARE比LRU替换提高了10.3%的IPC。在存在更多并发数据访问的8核和16核系统中，CARE分别比LRU高出13.0%和17.1%。
Improving cache performance is a lasting research topic. While utilizing data locality to enhance cache performance becomes more and more difficult, data access concurrency provides a new opportunity for cache performance optimization. In this work, we propose a novel concurrency-aware cache management framework that outperforms state-of-the-art locality-only cache management schemes. First, we investigate the merit of data access concurrency and pinpoint that reducing the miss rate may not necessarily lead to better overall performance. Next, we introduce the pure miss contribution (PMC) metric, a lightweight and versatile concurrency-aware indicator, to accurately measure the cost of each outstanding miss access by considering data concurrency. Then, we present CARE, a dynamic adjustable, concurrency-aware, low-overhead cache management framework with the help of the PMC metric. We evaluate CARE with extensive experiments across different application domains and show significant performance gains with the consideration of data concurrency. In a 4-core system, CARE improves IPC by 10.3% over LRU replacement. In 8 and 16-core systems where more concurrent data accesses exist, CARE outperforms LRU by 13.0% and 17.1%, respectively.