Title :
Evolution, entropy, and parallel computation
Author_Institution :
Thinking Machines Corp., Cambridge, MA, USA
Abstract :
The relationship between evolution and entropy is described for a model of self-reproducing parallel computation. As was recently shown by Thearling and Ray (1994), the performance of some types of parallel computation can be increased though a process analogous to evolution by natural selection. The work discussed in this paper explores the process by which evolution manipulates the entropy of instruction sequences in a population of parallel programs in an effort to discover more efficient uses of parallelism
Keywords :
entropy; genetic algorithms; information theory; parallel algorithms; self-reproducing automata; computational performance; efficient uses; entropy; evolution; instruction sequences; natural selection; parallel program population; parallelism; self-reproducing parallel computation; Bioinformatics; Concurrent computing; Entropy; Evolution (biology); Genomics; Organisms; Parallel processing; Parallel programming; Sequences; Writing;
Conference_Titel :
Physics and Computation, 1994. PhysComp '94, Proceedings., Workshop on
Conference_Location :
Dallas, TX
Print_ISBN :
0-8186-6715-X
DOI :
10.1109/PHYCMP.1994.363674
