Constraint Based System-Level Diagnosis of Multiprocessors

Abstract

The paper presents a novel modelling technique for system-level fault diagnosis in massive parallel multiprocessors, based on a re-formulation of the problem of syndrome decoding to a constraint satisfaction problem (CSP). The CSP based approach is able to handle detailed and inhomogeneous functional fault models to a similar depth as the Russel-Kime model [18]. Multiple-valued logic is used to deal with system components having multiple fault modes. The granularity of the models can be adjusted to the target diagnostic resolution without altering the methodology. Two algorithms for the Parsytec GCel massively parallel system are used as illustration in the paper: the centralized method uses a detailed system model, and provides a fine-granular diagnostic image for off-line evaluation. The distributed method makes fast decisions for reconfiguration control, using a simplified model.