Algorithm-Based Fault-tolerant Programming in Scientific Computation on Multiprocessors

Abstract

Efficient parallel algorithms proposed to solve many fundamental problems in scientific computation are sensitive to processor failures. Because of its low costs, algorithm-based fault tolerance is an interesting concept for introducing fault tolerance into existing multiprocessors. To facilitate fault-tolerant programming in scientific computation, we have modified and developed further an existing parallel run-time environment. In this paper the aspect of tuning known error processing techniques to the algorithm-based approach is primarily examined. Design issues for implementation and execution time overhead of a fault-tolerant application in our run-time environment are studied. In contrast to many other environments for parallel fault-tolerant programming, which use the master/slave programming model, our environment enables one to add fault tolerance to existing parallel applications in scientific computation