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.

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