History-Assisted Adaptive-Granularity Caches (HAAG$) for High Performance 3D DRAM Architectures
History-Assisted Adaptive-Granularity Caches (HAAG$) for High Performance 3D DRAM Architectures
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用于高性能 3D DRAM 架构的历史辅助自适应粒度缓存 (HAAG$)
DOI：
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发表时间：
2015
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通讯作者：
N. Jouppi
中科院分区：
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作者：
Ke Chen;Sheng Li;Jung Ho Ahn;N. Muralimanohar;Jishen Zhao;Cong Xu;O. Seongil;Yuan Xie;J. Brockman;N. Jouppi
三维堆叠 DRAM 有潜力为未来的高性能计算系统和数据中心提供高性能和大容量内存，而专用逻辑芯片的集成也为 DRAM 行缓冲存储器等架构增强提供了机会。然而，对于 3D 存储系统来说，高性能和高性价比的行缓冲存储器设计仍然具有挑战性。在本文中，我们提出了历史辅助自适应粒度高速缓存（HAAG$），它采用自适应高速缓存方案来支持不同粒度的全关联性，并采用智能历史辅助预测器来支持 3D 存储系统中的大量存储库。通过提高行缓冲区缓存命中率和避免不必要的数据缓存，HAAG$ 显著降低了内存访问延迟和动态功耗。我们的设计尤其适用于运行（不规则）内存密集型应用的多核 CPU，在这种情况下，很难利用内存本地性。评估结果表明，在内存密集型 CPU 工作负载中，HAAG$ 的性能比最先进的行缓冲缓存高出 33.5%。
3D-stacked DRAM has the potential to provide high performance and large capacity memory for future high performance computing systems and datacenters, and the integration of a dedicated logic die opens up opportunities for architectural enhancements such as DRAM row-buffer caches. However, high performance and cost-effective row-buffer cache designs remain challenging for 3D memory systems. In this paper, we propose History-Assisted Adaptive-Granularity Cache (HAAG$) that employs an adaptive caching scheme to support full associativity at various granularities, and an intelligent history-assisted predictor to support a large number of banks in 3D memory systems. By increasing the row-buffer cache hit rate and avoiding unnecessary data caching, HAAG$ significantly reduces memory access latency and dynamic power. Our design works particularly well for manycore CPUs running (irregular) memory intensive applications where memory locality is hard to exploit. Evaluation results show that with memory-intensive CPU workloads, HAAG$ can outperform the state-of-the-art row buffer cache by 33.5%.