Document Type

Conference Proceeding

Language

eng

Format of Original

8 p.

Publication Date

10-2013

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Source Publication

42nd International Conference on Parallel Processing (ICPP) 2013

Source ISSN

0190-3918

Original Item ID

doi: 10.1109/ICPP.2013.98

Abstract

Improving energy efficiency is an ongoing challenge in HPC because of the ever-increasing need for performance coupled with power and economic constraints. Though GPU-accelerated heterogeneous computing systems are capable of delivering impressive performance, it is necessary to explore all available power-aware technologies to meet the inevitable energy efficiency challenge. In this paper, we experimentally study the impacts of DVFS on application performance and energy efficiency for GPU computing and compare them with those of DVFS for CPU computing. Based on a power-aware heterogeneous system that includes dual Intel Sandy Bridge CPUs and the latest Nvidia K20c Kepler GPU, the study provides numerous new insights, general trends and exceptions of DVFS for GPU computing. In general, the effects of DVFS on a GPU differ from those of DVFS on a CPU. For example, on a GPU running compute-bound high-performance and high-throughput workloads, the system performance and the power consumption are approximately proportional to the GPU frequency. Hence, with a permissible power limit, increasing the GPU frequency leads to better performance without incurring a noticeable increase in energy. This paper further provides detailed analytical explanations of the causes of the observed trends and exceptions. The findings presented in this paper have the potential to impact future CPU and GPU architectures to achieve better energy efficiency and point out directions for designing effective DVFS schedulers for heterogeneous systems.

Comments

Accepted version. Published as part of the proceedings of the conference, 42nd International Conference on Parallel Processing (ICPP) 2013, 2013: 826-833. DOI. © 2013 IEEE. Reprinted, with permission, from Rong Ge et al., "Effects of Dynamic Voltage and Frequency Scaling on a K20 GPU", 42nd International Conference on Parallel Processing (ICPP) 2013, October 2013.

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