Effective approximate fault diagnosis of systems with inhomogeneous test invalidation

Abstract

System-level fault diagnosis is a methodology to identify, the failed components in a multiprocessor system. The traditional approach to system-level diagnosis does not take into consideration many important aspects of modern multiprocessor architectures. This paper examines a special class of multiprocessors, called massively parallel computers. As a practical example, the Parsytec GCel system is presented. The paper describes a new method developed for the Parsytec GCel, called local information diagnosis. The diagnostic algorithm is based on the generalized test invalidation model, therefore it is applicable to a wide range of systems, including inhomogeneous ones. Due to the employed syndrome decoding mechanism, the space and computational complexity of the algorithm is also smaller than in conventional methods.