The case for reconfigurable general purpose GPU computing

General purpose graphics processing unit (GPU) computing (GPGPU) has emerged as a new paradigm for programmers to exploit massive amounts of parallelism for relatively low costs. The abundance of GPUs in desktop and mobile computing platforms makes them ideal for accelerating tasks on multiple devices. However, despite the massively parallel architecture, GPUs are limited by the applications that run on them. The generic architecture of a GPU allows it to accelerate a large variety of applications, but none of these applications are capable of exploiting the complete performance capabilities of the GPU. This underutilization results in wastage of resources and power. In this work, we propose to introduce reconfiguration to the GPU architecture in the hopes of being able to tune its architecture to maximize performance for a given application or redistribute resources so as to reduce power consumption.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Dhar, Ashutosh

Contributors dc:contributor

• Chen, Deming

• Graphics Processing Unit (GPU)
• General Purpose Graphics Processing Unit (GPGPU)
• Reconfigurable Computing
• Architecture
• Compute Unified Device Architecture (CUDA)

Statement dc:rights

• Copyright 2014 Ashutosh Dhar

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/73103

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/73103