Title :
The ARGOT strategy III: the BBN Butterfly multiprocessor
Author :
O´Neil, E.J. ; Shaefer, Craig G.
Author_Institution :
Dept. of Math. & Comput. Sci., Massachusetts Univ., Boston, MA, USA
Abstract :
The ARGOT strategy combines genetic algorithms with a mechanism providing a dynamically adaptive representation to form a robust optimization tool, as previously shown in the uniprocessor environment. For implementation of ARGOT on the BBN Butterfly multiprocessor, a parallel selection algorithm and a method of incremental payoff update were developed. These lead to enhanced parallelism and reduced the amount of computation needed by any genetic algorithms, including ARGOT. Experimental results on two matrix problems are presented, one a linear system from a FEM problem, and the other a nonlinear problem not well-behaved enough for consistent conjugate gradient results
Keywords :
finite element analysis; multiprocessing systems; structural engineering computing; ARGOT strategy III; BBN Butterfly multiprocessor; FEM; dynamically adaptive representation; genetic algorithms; matrix problems; nonlinear problem; parallel selection algorithm; robust optimization tool; Biological cells; Biological information theory; Evolution (biology); Genetic algorithms; Genetic mutations; Scheduling algorithm; Search methods; Space exploration; Stochastic processes; Symbiosis;
Conference_Titel :
Supercomputing 88. Vol.II: Science and Applications., Proceedings
Conference_Location :
Orlando, FL
Print_ISBN :
0-8186-8923-4
DOI :
10.1109/SUPERC.1988.74147
