16 Scopus citations


This short note considers the applicability of algorithm-based fault tolerance (ABFT) to massively parallel scientific computation. Existing ABFT 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 ABFT 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.

Original languageEnglish (US)
Pages (from-to)649-653
Number of pages5
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number6
StatePublished - Jun 1994

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics


  • Algorithm-based fault tolerance
  • checksum code
  • detection
  • error
  • error correction
  • transient errors


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