Reducing Data Movement and Energy in Multilevel Cache Hierarchies without Losing Performance: Can you have it all?

2019 28th International Conference on Parallel Architectures and Compilation Techniques (PACT)(2019)

引用 3|浏览38
暂无评分
摘要
Optimizing a multilayer cache hierarchy involves a careful balance of data placement, replacement, promotion, bypassing, prefetching, etc. to capture the various properties of access streams. Often getting good performance involves aggressively orchestrating the movement of the data to be available at the appropriate layers of the cache hierarchy at appropriate times. However, it has been popularly recognized that aggressive movement of data results in high energy consumption. State-of-the-art caching policies such as Hawkeye and MPPPB yield excellent performance but incur more data movement compared to policies such as CHAR, and Flexclusion. Considering the energy cost of data movement, we architect a FILtered Multilevel (FILM) caching policy, which yields good performance with reduced levels of data movement. It achieves this by identifying appropriate cache layers for each block of data using a bloom filter and table based predictors. The bloom filter helps to overcome the challenges associated with capturing PC-based information in exclusive caches in an efficient manner. When there is free space in the bypassed cache layer, FILM overrides the initial prediction and allows cache block installation into the cache level achieving more low latency hits. FILM also incorporates an explicit mechanism for handling prefetches, which allows it to train differently for data from demand requests versus prefetch requests. By incorporating quick detection and correction of stale/incorrect bypass decisions, FILM significantly reduces cache block installations and data movement, resulting in up to 10% reduction in dynamic energy at the LLC and DRAM compared with Hawkeye EX or MPPPB EX. Considering energy-delay product as a metric, FILM is 10%, 11%, and 5% better than Hawkeye EX, MPPPB EX, and CHAR respectively.
更多
查看译文
关键词
Cache subsystem,Energy,Memory hierarchy
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要