Cuttlefish: Library for Achieving Energy Efficiency in Multicore Parallel Programs

被引:6
作者
Kumar, Sunil [1 ]
Gupta, Akshat [1 ]
Kumar, Vivek [1 ]
Bhalachandra, Sridutt [2 ]
机构
[1] IIIT Delhi, Delhi, India
[2] Lawrence Berkeley Natl Lab, Berkeley, NJ USA
来源
SC21: INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS | 2021年
基金
美国国家科学基金会;
关键词
Multicore parallelism; DVFS; UFS; energy efficiency; SYSTEM;
D O I
10.1145/3458817.3476163
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
A low-cap power budget is challenging for exascale computing. Dynamic Voltage. and freqtrency Scaling (DNTS) and Uncore freqtrency Scaling (LIPS) are the two widely used techniques for limiting the IIPC application's energy footprint. However, existing approaches fail to provide a unified solution that can work with different types of parallel programming models and applications. This paper proposes ClatIefish, a programming model oblivious C/C++ library for achieving energy efficiency in rnulticore parallel programs running over Intel processors. An online profiler periodically profiles model specific registers to discover a running application's memory access pattern. Using a combination of DVFS and UFS, Cuttlefish then dynamically adapts the processor's core and uncore frequencies, thereby improving its energy efficiency. The evaluation on a 20-core Intel Xeon processor using a set of widely used OpenMP benchmarks, consisting of several irregular-tasking and work -sharing pragmas, achieves geometric mean energy savings of 19.4% with a 3.6% slowdown.
引用
收藏
页数:14
相关论文
共 53 条
[1]  
[Anonymous], MANTEVO PERFORMANCE
[2]  
[Anonymous], 2005, Proc. of the tenth ACM SIGPLAN symposium on Principles and Practice of Parallel Programming (PPoPP'05), Chicago, IL
[3]  
[Anonymous], 2020, TOP500
[4]   Workload-Aware Runtime Energy Management for HPC Systems [J].
Basireddy, Karunakar R. ;
Wachter, Eduardo W. ;
Al-Hashimi, Bashir M. ;
Merrett, Geoff V. .
PROCEEDINGS 2018 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING & SIMULATION (HPCS), 2018, :292-299
[5]   ML GUIDED ENERGY-PERFORMANCE TRADE-OFF ESTIMATION FOR UNCORE FREQUENCY SCALING [J].
Bekele, Solomon Abera ;
Balakrishnan, M. ;
Kumar, Anshul .
2019 SPRING SIMULATION CONFERENCE (SPRINGSIM), 2019,
[6]  
Bhalachandra S., 2017, P 5 INT WORKSHOP ENE, P6, DOI DOI 10.1145/3149412.3149418
[7]   An Adaptive Core-specific Runtime for Energy Efficiency [J].
Bhalachandra, Sridutt ;
Porterfield, Allan ;
Olivier, Stephen L. ;
Prins, Jan F. .
2017 31ST IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM (IPDPS), 2017, :947-956
[8]   Using Dynamic Duty Cycle Modulation to improve energy efficiency in High Performance Computing [J].
Bhalachandra, Sridutt ;
Porterfield, Allan ;
Prins, Jan F. .
2015 IEEE 29TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS, 2015, :911-918
[9]  
Bull JM, 2000, CONCURRENCY-PRACT EX, V12, P375, DOI 10.1002/1096-9128(200005)12:6<375::AID-CPE480>3.0.CO
[10]  
2-M