An accelerated parallel algorithm for constructing the nonredundant matrix of implications during the construction of fault-tolerant nonredundant diagnostic tests

Abstract

In this article the relevance of using test methods of pattern recognition while developing intelligent systems for decision making support for various problem areas is discussed. The advantage of fault-tolerant diagnostic tests used in intelligent systems is shown, namely, a tool for registering and processing different kinds of errors in databases and knowledge bases. The results of testing two algorithms for constructing the nonredundant matrix of implications are compared; the technical particulars of program implementation are discussed such as synchronization means, test environment, test-program structure, and bottlenecks of program implementation; methods of their elimination, and further development of parallel algorithms.