Fault–Tolerant High–Performance Matrix Multiplication
John A. Gunnels, Daniel S. Katz, Enrique S. Quintana–Ort́ı, Robert A. Geijn · 2004
In this paper, we extend the theory of 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 theoretically show that the methods will detect all errors as long as only one entry is corrupted. Third, we propose a low-overhead rollback 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 the methods work well in practice with an acceptable level of overhead relative to high-performance implementations without fault-tolerance.