Date of Award:

2016

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Electrical and Computer Engineering

Advisor/Chair:

Koushik Chakraborty

Abstract

The evolution of the Graphics Processing Units (GPUs) over the last decade, has reinforced general purpose computing while sustaining a steady performance growth in graphics intensive applications. However, the immense performance improvement is generally associated with a steep rise in GPU power consumption. Consequently, GPUs are already close to the abominable power wall. With a massive popularity of the mobile devices running general-purpose GPU (GPGPU) applications, it is of utmost importance to ensure a high energy efficiency, while meeting the strict performance requirements.

In this work, we demonstrate that, customizing a Streaming Multiprocessor (SM) of a GPU, at a lower frequency, is significantly more energy efficient, compared to employing Dynamic Voltage and Frequency Scaling (DVFS) on an SM, designed for a high frequency operation. Using a system level Computer Aided Design (CAD) technique, we propose SSAGA - Streaming Multiprocessors Sculpted for Asymmetric GPGPU Applications, an energy efficient GPU design paradigm. SSAGA creates architecturally identical SM cores, customized for different voltage-frequency domains.

Checksum

5d2ed8773a91c81b7a123884c52fca8e

Download

Share

COinS

Copyright for this work is retained by the student. If you have any questions regarding the inclusion of this work in the Digital Commons, please email us at .