Efficient Selective Multicore Prefetching under Limited Memory Bandwidth

[EN] Current multicore systems implement multiple hardware prefetchers to tolerate long main memory latencies. However, memory bandwidth is a scarce shared resource which becomes critical with the increasing core count. To deal with this fact, recent works have focused on adaptive prefetchers, which control the prefetcher aggressiveness to regulate the main memory bandwidth consumption. Nevertheless, in limited bandwidth machines or under memory-hungry workloads, keeping active the prefetcher can damage the system performance and increase energy consumption. This paper introduces selective prefetching, where individual prefetchers are activated or deactivated to improve both main memory energy and performance, and proposes ADP, a prefetcher that deactivates local prefetchers in some cores when they present low performance and co-runners need additional bandwidth. Based on heuristics, an individual prefetcher is reactivated when performance enhancements are foreseen. Compared to a state-of-the-art adaptive prefetcher, ADP provides both performance and energy enhancements in limited memory bandwidth. (C) 2018 Elsevier Inc. All rights reserved.Selfa-Oliver, V.; Sahuquillo Borrás, J.; Gómez Requena, ME.; Gómez Requena, C. (2018). Efficient Selective Multicore Prefetching under Limited Memory Bandwidth. Journal of Parallel and Distributed Computing. 120:32-43. https://doi.org/10.1016/j.jpdc.2018.05.002S324312