Abstract
A new approach to the design of parallel genetic algorithms (GA) for execution in distributed systems is presented. It is based on the use of global parallel program control functions and asynchronous process/thread internal execution control based on global application states monitoring. A control design graphical infrastructure is provided for a programmer based on generalized synchronization processes called synchronizers. They collect local states of program elements, compute global control predicates and send control signals to program computational elements. It enables an easy construction and management of global program states for the purpose of the program execution control at both thread and process level. At each level we create a hierarchical control/synchronization infrastructure which is used to optimize the control of computations in programs. As an example we present the design of a parallel genetic algorithm used to partition a macro data flow graph for FDTD (Finite Difference Time Domain method) computations.
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Smyk, A., Tudruj, M. (2012). A Parallel Genetic Algorithm Based on Global Program State Monitoring. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2011. Lecture Notes in Computer Science, vol 7203. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31464-3_40
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DOI: https://doi.org/10.1007/978-3-642-31464-3_40
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