—Computational performance increasingly depends on parallelism, and many systems rely on heterogeneous resources such as GPUs and FPGAs to accelerate computationally intensive ap...
Marcin Bogdanski, Peter R. Lewis, Tobias Becker, X...
Abstract. This paper describes GAPP – a framework for the execution of distributed genetic algorithms (GAs) using the H2O metacomputing environment. GAs may be a viable solution ...
Tomasz Ampula, Dawid Kurzyniec, Vaidy S. Sunderam,...
Minimization of the execution time of an iterative application in a heterogeneous parallel computing environment requires an appropriate mapping scheme for matching and scheduling...
Yu-Kwong Kwok, Anthony A. Maciejewski, Howard Jay ...
Solving the structure prediction problem for complex proteins is difficult and computationally expensive. In this paper, we propose a bicriterion parallel hybrid genetic algorith...
Physical map reconstruction in the presence of errors is a central problem in genetics of high computational complexity. A parallel genetic algorithm for a maximum likelihood esti...
Suchendra M. Bhandarkar, Jinling Huang, Jonathan A...