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Tradeoffs in the design of efficient algorithm-based error detection schemes for hypercube multiprocessors

机译:超立方体多处理器的基于算法的高效错误检测方案设计中的权衡

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The authors provide an in-depth study of the various issues and tradeoffs available in algorithm-based error detection, as well as a general methodology for evaluating the schemes. They illustrate the approach on an extremely useful computation in the field of numerical linear algebra: QR factorization. They have implemented and investigated numerous ways of applying algorithm-based error detection using different system-level encoding strategies for QR factorization. Specifically, schemes based on the checksum and sum-of-squares (SOS) encoding techniques have been developed. The results of studies performed on a 16-processor Intel iPSC-2/D4/MX hypercube multiprocessor are reported. It is shown that, in general, the SOS approach gives much better coverage (85-100%) for QR factorization while maintaining low overheads (below 10%).
机译:作者提供了对基于算法的错误检测中可用的各种问题和折衷的深入研究,以及评估方案的通用方法。他们说明了在数值线性代数领域中极为有用的计算方法:QR因式分解。他们已经实施并研究了使用不同的系统级编码策略进行QR分解的多种基于算法的错误检测方法。具体地,已经开发了基于校验和和平方和(SOS)编码技术的方案。报告了在16处理器Intel iPSC-2 / D4 / MX超立方体多处理器上执行的研究结果。结果表明,一般而言,SOS方法可为QR因式分解提供更好的覆盖率(85-100%),同时保持较低的开销(低于10%)。

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