A Survey of Methods For Analyzing and Improving GPU Energy Efficiency

TL;DR

This survey reviews recent research on analyzing and enhancing GPU energy efficiency, classifies various techniques, and compares GPU power management with other computing systems to guide future developments.

Contribution

It provides a comprehensive classification of GPU energy efficiency methods and synthesizes comparative analyses with FPGAs and CPUs, aiding researchers in advancing energy-efficient GPU architectures.

Findings

Classification of energy efficiency techniques

Comparison of GPU with FPGAs and CPUs

Identification of research gaps and future directions

Abstract

Recent years have witnessed a phenomenal growth in the computational capabilities and applications of GPUs. However, this trend has also led to dramatic increase in their power consumption. This paper surveys research works on analyzing and improving energy efficiency of GPUs. It also provides a classification of these techniques on the basis of their main research idea. Further, it attempts to synthesize research works which compare energy efficiency of GPUs with other computing systems, e.g. FPGAs and CPUs. The aim of this survey is to provide researchers with knowledge of state-of-the-art in GPU power management and motivate them to architect highly energy-efficient GPUs of tomorrow.