Dependable parallel computing with agents based on a task graph model

We discuss a novel technique for improving the dependability of parallel programs executing on a MIMD shared memory architecture. The idea is to empower certain tasks of each application program to carry out failure detection, and to reschedule the execution of those tasks which are considered to have failed. The technique we propose is based on a task graph representation of the parallel program, in which communications between tasks have been voluntarily isolated to the end of each task which is being considered. We propose and evaluate several algorithms which can detect failures and restart failed tasks. A discrete-event simulator is used to evaluate the performance under the effect of failures, with the use of our detection and restart algorithms, of a specific parallel application: the fast Fourier transform