Exploiting Data-Flow for Fault-Tolerance in a Wide-Area Parallel System

Abstract

Wide-area parallel processing systems will soon be available to researchers to solve a range of problems. In these systems, it is certain that host failures and other faults will be a common occurrence. Unfortunateb, most parallel processing systems have not been designed with fault-tolerance in mind. Mentat is a high-performance objec t-oriented parallel processing system that is based on an extension of the data-flow model. The functional nature of data-flow enabies both parallelism and faulttolerance. In this paper, we exploit the data-flow underpinning of Mentat to provide easy-to-use and transparent fault-tolerance. We present results on both a small-scale network and a wide-area heterogeneous environment that consists of three sites: the National Center for Supercomputing Applications, the University of Mrginia and the NASA Langley Research Center.

Self-Adaptation of Parallel Applications in Heterogeneous and Dynamic Architectures

“…A data flow graph [10] allows for a natural representation of a parallel execution, and it can be exploited to achieve fault-tolerance [9]. By the principle of data flow, tasks become ready for execution upon availability of their input data.…”