TY - GEN
T1 - Power and energy footprint of OpenMP programs using OpenMP runtime API
AU - Nandamuri, Anilkumar
AU - Malik, Abid M.
AU - Qawasmeh, Ahmad
AU - Chapman, Barbara M.
N1 - Publisher Copyright: © 2014 IEEE.
PY - 2015/1/20
Y1 - 2015/1/20
N2 - Power and energy have become dominant aspects of hardware and software design in the High Performance Computing (HPC). Recently, the Department of Defense (DOD) has put a constraint that applications and architectures need to attain 75 GFLOPS/Watt in order to support the future missions. This requires a significant research effort towards power and energy optimization. OpenMP programming model is an integral part of HPC. Comprehensive analysis of OpenMP programs for power and execution performance is an active research area. Work has been done to characterize OpenMP programs with respect to power performance at kernel level. However, no work has been done at the OpenMP event level. OpenMP Runtime API (ORA), proposed by the OpenMP standard committee, allow a performance tool to collect information at the OpenMP event level. In this paper, we present a comprehensive analysis of the OpenMP programs using ORA for power and execution performance. Using hardware counters in the Intel SandyBridge x86-64 and Running Average Power Limit (RAPL) energy sensors, we measure power and energy characteristics of OpenMP benchmarks. Our results show that the best execution performance does not always give the best energy usage. We also find out that the waiting time at the barriers and in queue are the main factors for high power consumption for a given OpenMP program. Our results also show that there are unique patterns at the fine level that can be used by the dynamic power management system to enhance the power performance. Our results show substantial variation in energy usage depending upon the runtime environment.
AB - Power and energy have become dominant aspects of hardware and software design in the High Performance Computing (HPC). Recently, the Department of Defense (DOD) has put a constraint that applications and architectures need to attain 75 GFLOPS/Watt in order to support the future missions. This requires a significant research effort towards power and energy optimization. OpenMP programming model is an integral part of HPC. Comprehensive analysis of OpenMP programs for power and execution performance is an active research area. Work has been done to characterize OpenMP programs with respect to power performance at kernel level. However, no work has been done at the OpenMP event level. OpenMP Runtime API (ORA), proposed by the OpenMP standard committee, allow a performance tool to collect information at the OpenMP event level. In this paper, we present a comprehensive analysis of the OpenMP programs using ORA for power and execution performance. Using hardware counters in the Intel SandyBridge x86-64 and Running Average Power Limit (RAPL) energy sensors, we measure power and energy characteristics of OpenMP benchmarks. Our results show that the best execution performance does not always give the best energy usage. We also find out that the waiting time at the barriers and in queue are the main factors for high power consumption for a given OpenMP program. Our results also show that there are unique patterns at the fine level that can be used by the dynamic power management system to enhance the power performance. Our results show substantial variation in energy usage depending upon the runtime environment.
KW - Energy
KW - OpenMP
KW - Performance Analysis
KW - Power
KW - Runtime API
UR - https://www.scopus.com/pages/publications/84923230534
U2 - 10.1109/E2SC.2014.11
DO - 10.1109/E2SC.2014.11
M3 - Conference contribution
T3 - Proceedings of E2SC 2014: 2nd International Workshop on Energy Efficient Supercomputing - Held in Conjunction with SC 2014: The International Conference for High Performance Computing, Networking, Storage and Analysis
SP - 79
EP - 88
BT - Proceedings of E2SC 2014 2nd International Workshop on Energy Efficient Supercomputing Held in Conjunction with the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Workshop on Energy Efficient Supercomputing, E2SC 2014 - Held in Conjunction with the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2014
Y2 - 16 November 2014
ER -