Program Optimization Strategies for Data-Parallel Many-Core Processors
Ryoo, Shane
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Permalink
https://hdl.handle.net/2142/81081
Description
Title
Program Optimization Strategies for Data-Parallel Many-Core Processors
Author(s)
Ryoo, Shane
Issue Date
2008
Doctoral Committee Chair(s)
Hwu, Wen-Mei W.
Department of Study
Electrical and Computer Engineering
Discipline
Electrical and Computer Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Language
eng
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.
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