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Hardware error detection in multicore parallel programs Wei, Jiesheng
Abstract
The scaling of Silicon devices has exacerbated the unreliability of modern computer systems, and power constraints have necessitated the involvement of software in hardware error detection. Simultaneously, the multi-core revolution has impelled software to become parallel. Therefore, there is a compelling need to protect parallel programs from hardware errors. Parallel programs’ tasks have significant similarity in control data due to the use of high-level programming models. In this thesis, we propose BlockWatch to leverage the similarity in parallel program’s control data for detecting hardware errors. BlockWatch statically extracts the similarity among different threads of a parallel program and checks the similarity at runtime. We evaluate BlockWatch on eight SPLASH-2 benchmarks to measure its performance overhead and error detection coverage. We find that BlockWatch incurs an average overhead of 15% across all programs, and provides an average SDC coverage of 97% for faults in the control data.
Item Metadata
Title |
Hardware error detection in multicore parallel programs
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2012
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Description |
The scaling of Silicon devices has exacerbated the unreliability of modern computer systems, and power constraints have necessitated the involvement of software in hardware error detection. Simultaneously, the multi-core revolution has impelled software to become parallel. Therefore, there is a compelling need to protect parallel programs from hardware errors.
Parallel programs’ tasks have significant similarity in control data due to the use of high-level programming models. In this thesis, we propose BlockWatch to leverage the similarity in parallel program’s control data for detecting hardware errors. BlockWatch statically extracts the similarity among different threads of a parallel program and checks the similarity at runtime. We evaluate BlockWatch on eight SPLASH-2 benchmarks to measure its performance overhead and error detection coverage. We find that BlockWatch incurs an average overhead of 15% across all programs, and provides an average SDC coverage of 97% for faults in the control data.
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Genre | |
Type | |
Language |
eng
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Date Available |
2012-08-17
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0073009
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2012-11
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International