Harnessing GPU computing in system-level software

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Publication Type dissertation
School or College College of Engineering
Department Computing
Author Sun, Weibin
Title Harnessing GPU computing in system-level software
Date 2014-08
Description As the base of the software stack, system-level software is expected to provide ecient and scalable storage, communication, security and resource management functionalities. However, there are many computationally expensive functionalities at the system level, such as encryption, packet inspection, and error correction. All of these require substantial computing power. What's more, today's application workloads have entered gigabyte and terabyte scales, which demand even more computing power. To solve the rapidly increased computing power demand at the system level, this dissertation proposes using parallel graphics pro- cessing units (GPUs) in system software. GPUs excel at parallel computing, and also have a much faster development trend in parallel performance than central processing units (CPUs). However, system-level software has been originally designed to be latency-oriented. GPUs are designed for long-running computation and large-scale data processing, which are throughput-oriented. Such mismatch makes it dicult to t the system-level software with the GPUs. This dissertation presents generic principles of system-level GPU computing developed during the process of creating our two general frameworks for integrating GPU computing in storage and network packet processing. The principles are generic design techniques and abstractions to deal with common system-level GPU computing challenges. Those principles have been evaluated in concrete cases including storage and network packet processing applications that have been augmented with GPU computing. The signicant performance improvement found in the evaluation shows the eectiveness and eciency of the proposed techniques and abstractions. This dissertation also presents a literature survey of the relatively young system-level GPU computing area, to introduce the state of the art in both applications and techniques, and also their future potentials.
Type Text
Publisher University of Utah
Subject GPU; Network; Storage; System software
Dissertation Institution University of Utah
Dissertation Name Doctor of Philosophy
Language eng
Rights Management Copyright © Weibin Sun 2014
Format Medium application/pdf
Format Extent 1,535,087 bytes
Identifier etd3/id/3214
ARK ark:/87278/s6p87m5t
Setname ir_etd
ID 196780
Reference URL https://collections.lib.utah.edu/ark:/87278/s6p87m5t