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Title:Program Optimization Strategies for Data-Parallel Many-Core Processors
Author(s):Ryoo, Shane
Doctoral Committee Chair(s):Hwu, Wen-Mei W.
Department / Program:Electrical and Computer Engineering
Discipline:Electrical and Computer Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Engineering, Electronics and Electrical
Abstract:My work discusses various strategies for optimizing programs on a highly data-parallel architecture with fine-grained sharing of resources. I first investigate useful strategies in optimizing a suite of applications. I then introduce program optimization carving, an approach that discovers high-performance application configurations for data-parallel, many-core architectures. Instead of applying a particular phase ordering of optimizations, it starts with an optimization space of major transformations and then reduces the space by examining the static code and pruning configurations that do not maximize desirable qualities in isolation or combination. Careful selection of pruning criteria for applications running on the NVIDIA GeForce 8800 GTX reduces the optimization space by as much as 98% while finding configurations within 1% of the best performance. Random sampling, in contrast, can require nearly five times as many configurations to find performance within 10% of the best. I also examine the technique's effectiveness when varying pruning criteria.
Issue Date:2008
Type:Text
Language:English
Description:146 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008.
URI:http://hdl.handle.net/2142/81081
Other Identifier(s):(MiAaPQ)AAI3314878
Date Available in IDEALS:2015-09-25
Date Deposited:2008


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