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ACM Transactions on Mathematical Software (TOMS)
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Journal of the ACM (JACM)
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ACM Transactions on Mathematical Software (TOMS)
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SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
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ICCS '01 Proceedings of the International Conference on Computational Sciences-Part I
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DSN '00 Proceedings of the 2000 International Conference on Dependable Systems and Networks (formerly FTCS-30 and DCCA-8)
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FTCS '99 Proceedings of the Twenty-Ninth Annual International Symposium on Fault-Tolerant Computing
Formal Linear Algebra Methods Environment (FLAME) Overview
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Algorithm-Based Fault Tolerance for Matrix Operations
IEEE Transactions on Computers
IEEE Transactions on Software Engineering
International Journal of High Performance Computing Applications
High Performance Computing Systems for Autonomous Spaceborne Missions
International Journal of High Performance Computing Applications
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ACM Transactions on Mathematical Software (TOMS)
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Proceedings of the international conference on Supercomputing
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Fault tolerant matrix-matrix multiplication: correcting soft errors on-line
Proceedings of the second workshop on Scalable algorithms for large-scale systems
Correcting soft errors online in LU factorization
Proceedings of the 22nd international symposium on High-performance parallel and distributed computing
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Abstract: In this paper, we extend the theory and practice regarding algorithmic fault-tolerant matrix-matrix multiplication, C = AB, in a number of ways. First, we propose low-overhead methods for detecting errors introduced not only in C but also in A and/or B. Second, we show that, theoretically, these methods will detect all errors as long as only one entry is corrupted. Third, we propose a low-overhead roll-back approach to correct errors once detected. Finally, we give a high-performance implementation of matrix-matrix multiplication that incorporates these error detection and correction methods. Empirical results demonstrate that these methods work well in practice while imposing an acceptable level of overhead relative to high-performance implementations without fault-tolerance.