Accelerating the SCE-UA Global Optimization Method Based on Multi-Core CPU and Many-Core GPU

Fast parallel genetic programming: multi-core CPU versus many-core GPU

Genetic Programming (GP) is a computationally intensive technique which is also highly parallel in nature. In recent years, significant performance improvements have been achieved over a standard GP CPU-based approach by harnessing the parallel computational power of many-core graphics cards which have hundreds of processing cores. This enables both fitness cases and candidate solutions to be e...

pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment

BACKGROUND Our previously published CUDA-only application PaSWAS for Smith-Waterman (SW) sequence alignment of any type of sequence on NVIDIA-based GPUs is platform-specific and therefore adopted less than could be. The OpenCL language is supported more widely and allows use on a variety of hardware platforms. Moreover, there is a need to promote the adoption of parallel computing in bioinforma...

Genetic programming and cellular automata for fast flood modelling on multi-core CPU and many-core GPU computers

Efficient parallelization of the genetic algorithm solution of traveling salesman problem on multi-core and many-core systems

Efficient parallelization of genetic algorithms (GAs) on state-of-the-art multi-threading or many-threading platforms is a challenge due to the difficulty of schedulation of hardware resources regarding the concurrency of threads. In this paper, for resolving the problem, a novel method is proposed, which parallelizes the GA by designing three concurrent kernels, each of which running some depe...

Accelerating Network Coding on Many-core GPUs and Multi-core CPUs

Network coding has recently been widely applied in various distributed systems for throughput improvement and/or resilience to network dynamics. However, the computational overhead introduced by network coding operations is not negligible and has become the obstacle for practical deployment of network coding. In this paper, we exploit the computing power of commodity many-core Graphic Processin...