Performance-reliability tradeoff analysis for multithreaded applications

Modern architectures become more susceptible to transient errors with the scale down of circuits. This makes reliability an increasingly critical concern in computer systems. In general, there is a tradeoff between system reliability and performance of multithreaded applications running on multicore...

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Bibliographic Details
Published in:Proceedings of the Conference on Design, Automation and Test in Europe pp. 893 - 898
Main Authors: Oz, Isil, Topcuoglu, Haluk Rahmi, Kandemir, Mahmut, Tosun, Oguz
Format: Conference Proceeding
Language:English
Published: San Jose, CA, USA EDA Consortium 12.03.2012
Series:ACM Conferences
Subjects:
Computer systems organization > Dependable and fault-tolerant systems and networks
General and reference > Cross-computing tools and techniques > Performance
Networks > Network performance evaluation
Theory of computation > Models of computation > Concurrency
Theory of computation > Models of computation > Concurrency > Parallel computing models
reliable parallel and distributed algorithms
multi-core architectures and support
ISBN:3981080181, 9783981080186
Online Access:Get full text
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Summary:Modern architectures become more susceptible to transient errors with the scale down of circuits. This makes reliability an increasingly critical concern in computer systems. In general, there is a tradeoff between system reliability and performance of multithreaded applications running on multicore architectures. In this paper, we conduct a performance-reliability analysis for different parallel versions of three data-intensive applications including FFT, Jacobi Kernel, and Water Simulation. We measure the performance of these programs by counting execution clock cycles, while the system reliability is measured by Thread Vulnerability Factor (TVF) which is a recently-proposed metric. TVF measures the vulnerability of a thread to hardware faults at a high level. We carry out experiments by executing parallel implementations on multicore architectures and collect data about the performance and vulnerability. Our experimental evaluation indicates that the choice is clear for FFT application and Jacobi Kernel. Transpose algorithm for FFT application results in less than 5% performance loss while the vulnerability increases by 20% compared to binary-exchange algorithm. Unrolled Jacobi code reduces execution time up to 50% with no significant change on vulnerability values. However, the tradeoff is more interesting for Water Simulation where nsquared version reduces the vulnerability values significantly by worsening the performance with similar rates compared to faster but more vulnerable spatial version.
ISBN:3981080181
9783981080186
DOI:10.5555/2492708.2492933