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Permanent link (DOI): https://doi.org/10.7939/R3K63B
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A compiler for parallel execution of numerical Python programs on graphics processing units Open Access
- Other title
- Type of item
- Degree grantor
University of Alberta
- Author or creator
- Supervisor and department
Amaral, Jose Nelson (Computing Science)
- Examining committee member and department
Cockburn, Bruce (Electrical and Computer Engineering)
Lu, Paul (Computing Science)
Department of Computing Science
- Date accepted
- Graduation date
Master of Science
- Degree level
Modern Graphics Processing Units (GPUs) are providing breakthrough performance for numerical computing at the cost of increased programming complexity. Current programming models for GPUs require that the programmer manually manage the data transfer between CPU and GPU. This thesis proposes a simpler programming model and introduces a new compilation framework to enable Python applications containing numerical computations to be executed on GPUs and multi-core CPUs.
The new programming model minimally extends Python to include type and parallel-loop annotations. Our compiler framework then automatically identifies the data to be transferred between the main memory and the GPU for a particular class of affine array accesses. The compiler also automatically performs loop transformations to improve performance on GPUs.
For kernels with regular loop structure and simple memory access patterns, the GPU code generated by the compiler achieves significant performance improvement over multi-core CPU codes.
- Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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