Parallelization of Bioinformatics Algorithm using Genetic Algorithm on Multicore platform

Abstract — Nowadays, multicore processor and GPUs have entered the mainstream of microprocessor development. Multicore processors are widely used across many application domains including general-purpose, embedded, network, digital signal processing and graphics. The amount of performance gained by the use of a multicore processor depends very much on the software algorithms and implementation. In particular, the possible gains are limited by the fraction of the software that can be parallelized to run on multiple cores simultaneously. With the popularity of multicore problems, how to make use of multicore computing resources to accelerate the traditional serial applications has become a common concern problem. Multicore processor architectures provide high computation power by providing multiple levels of parallelism. It is a well known fact that genetic algorithms (GAs) are ideal for parallel computers due to their ability to parallel evaluate population members. Generally, the population can be split into several sub-populations and can execute them in parallel to speed up the processing of generation of population. In the field of Bioinformatics, for computation of larger data sets as well as for complex algorithms, such recent advance in the computer architecture help to provide optimal solution in short time. In this paper, we have given the proposed work about parallelism of complex bioinformatics algorithm using parallel genetic algorithm. Keywords- multicore architecture, parallel genetic algorithm, bioinformatics algorithm. I