Issue No. 06 - June (1994 vol. 5)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/71.285610
<p>Considers the applicability of algorithm based fault tolerance (ABET) to massively parallel scientific computation. Existing ABET schemes can provide effective fault tolerance at a low cost For computation on matrices of moderate size; however, the methods do not scale well to floating-point operations on large systems. This short note proposes the use of a partitioned linear encoding scheme to provide scalability. Matrix algorithms employing this scheme are presented and compared to current ABET schemes. It is shown that the partitioned scheme provides scalable linear codes with improved numerical properties with only a small increase in hardware and time overhead.</p>
Index Termsfault tolerant computing; software reliability; error correction codes; error detectioncodes; parallel architectures; matrix algebra; algorithm based fault tolerance; massivelyparallel systems; partitioned encoding; ABET; scalability; matrix algorithms; partitionedscheme; checksum code; error detection; error correction; transient errors
N. Jha and J. Rexford, "Partitioned Encoding Schemes for Algorithm-Based Fault Tolerance in Massively Parallel Systems," in IEEE Transactions on Parallel & Distributed Systems, vol. 5, no. , pp. 649-653, 1994.