Solutions to Parallel and Distributed Computing Problems: Lessons from Biological Sciences
Solving problems in parallel and distributed computing through the use of bio-inspired techniques. Recent years have seen a surge of interest in computational methods patterned after natural phenomena, with biologically inspired techniques such as fuzzy logic, neural networks, simulated annealing, genetic algorithms, or evolutionary computer models increasingly being harnessed for problem solving in parallel and distributed computing. Solutions to Parallel and Distributed Computing Problems presents a comprehensive review of the state of the art in the field, providing researchers and practitioners with critical information on the use of bio-inspired techniques for improving software and hardware design in high-performance computing. [From the back cover]
Digital Communications and Networking | Software Engineering | Theory and Algorithms
Zomaya, Albert Y. (Editor); Ercal, Fikret (Editor); and Olariu, Stephan (Editor), "Solutions to Parallel and Distributed Computing Problems: Lessons from Biological Sciences" (2000). Computer Science Faculty Books. 4.