In this paper we introduce an efficient implementation of asynchronously parallel genetic algorithm with adaptive genetic operators. The classic genetic algorithm paradigm is exte...
Data locality is critical to achievinghigh performance on large-scale parallel machines. Non-local data accesses result in communication that can greatly impact performance. Thus ...
FPGAs (Field-Programmable Gate Arrays) are often used as coprocessors to boost the performance of dataintensive applications [1, 2]. However, mapping algorithms onto multimillion-...
Abstract-- Genetic Parallel Programming (GPP) evolves parallel programs for MIMD architectures with multiple arithmetic/logic processors (MAPs). This paper describes a tool intende...
— Fuzzy Cognitive Maps (FCMs) are a class of discrete-time Artificial Neural Networks that are used to model dynamic systems. A recently introduced supervised learning method, wh...