@inproceedings{9efb11804cf241898e65da299e8c5ff0,
title = "Split Wisely: When Work Partitioning is Energy-Optimal on Heterogeneous Hardware",
abstract = "Heterogeneous System-on-Chip (SoC) processors are increasingly gaining traction in the High Performance Computing (HPC) community as alternate building blocks for future exascale systems. Key issues relating to their promise of energy efficiency include i) absolute performance, ii) finding an energy-optimal balance in the use of different on-chip devices and iii) understanding the performance-energy trade-offs while using different on-chip devices. In this paper we explore these issues through an energy usage model designed to predict the existence of an energy-optimal work partition between different processing elements on heterogeneous systems for any application. We validate our model by measuring performance and energy consumption of matrix multiplication on the NVIDIA Tegra K1 and X1 systems. An environment for monitoring and responding to energy usage is also outlined and used to perform high resolution measurements. Comparisons are drawn with conventional HPC systems housing Intel Xeon CPUs alongside NVIDIA GPUs.",
keywords = "Energy efficiency, Energy usage model, Haswell, Intel, K20, K80, Load balancing, NVIDIA, Power Measurement, Sandy bridge, SoC, Tegra K1, Tegra X1, UCurrent",
author = "Gaurav Mitra and Andrew Haigh and Anish Varghese and Luke Angove and Rendell, {Alistair P.}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016 ; Conference date: 12-12-2016 Through 14-12-2016",
year = "2017",
month = jan,
day = "20",
doi = "10.1109/HPCC-SmartCity-DSS.2016.0113",
language = "English",
series = "Proceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "781--788",
editor = "Yang, {Laurence T.} and Jinjun Chen",
booktitle = "Proceedings - 18th IEEE International Conference on High Performance Computing and Communications, 14th IEEE International Conference on Smart City and 2nd IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2016",
address = "United States",
}