More Bang for Your Buck:Boosting Performance with Capped Power Consumption  

作　　者：Juan Chen Xinxin Qi Feihao Wu Jianbin Fang Yong Dong Yuan Yuan Zheng Wang Keqin Li 

机构地区：[1]College of Computer,National University of Defense Technology,Changsha 410073,China [2]College of Computer,University of Leeds,London LS29JT,UK [3]School of Science and Engineering,State University of New York,New York,NY 12561,USA

出　　处：《Tsinghua Science and Technology》2021年第3期370-383,共14页清华大学学报（自然科学版（英文版）

基　　金：supported in part by the Advanced Research Project of China(No.31511010203);the Research Program of NUDT(No.ZK18-03-10)。

摘　　要：Achieving faster performance without increasing power and energy consumption for computing systems is an outstanding challenge.This paper develops a novel resource allocation scheme for memory-bound applications running on High-Performance Computing(HPC)clusters,aiming to improve application performance without breaching peak power constraints and total energy consumption.Our scheme estimates how the number of processor cores and CPU frequency setting affects the application performance.It then uses the estimate to provide additional compute nodes to memory-bound applications if it is profitable to do so.We implement and apply our algorithm to 12 representative benchmarks from the NAS parallel benchmark and HPC Challenge(HPCC)benchmark suites and evaluate it on a representative HPC cluster.Experimental results show that our approach can effectively mitigate memory contention to improve application performance,and it achieves this without significantly increasing the peak power and overall energy consumption.Our approach obtains on average 12.69%performance improvement over the default resource allocation strategy,but uses 7.06%less total power,which translates into 17.77%energy savings.

关 键 词：energy efficiency high-performance computing performance boost power control processor frequency scaling 

分 类 号：TP302[自动化与计算机技术—计算机系统结构]