Parallel Scientific Computing in C++ and MPI
Parallel Scientific Computing in C++ and MPI
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
A Swarm-Based Volition/Attention Framework for Object Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
An Efficient Fine-grained Parallel Genetic Algorithm Based on GPU-Accelerated
NPC '07 Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops
What else is the evolution of PSO telling us?
Journal of Artificial Evolution and Applications - Particle Swarms: The Second Decade
Hardware-oriented Adaptation of a Particle Swarm Optimization Algorithm for Object Detection
DSD '08 Proceedings of the 2008 11th EUROMICRO Conference on Digital System Design Architectures, Methods and Tools
Human body pose estimation with particle swarm optimisation
Evolutionary Computation
GPU-Based Road Sign Detection Using Particle Swarm Optimization
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
GPU-based parallel particle swarm optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Swarm's flight: accelerating the particles using C-CUDA
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A study of particle swarm optimization particle trajectories
Information Sciences: an International Journal
Parallel asynchronous control strategy for target search with swarm robots
International Journal of Bio-Inspired Computation
Parallelism and evolutionary algorithms
IEEE Transactions on Evolutionary Computation
A study on scale factor in distributed differential evolution
Information Sciences: an International Journal
GPU-based asynchronous particle swarm optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Collaborative multi-swarm PSO for task matching using graphics processing units
Proceedings of the 13th annual conference on Genetic and evolutionary computation
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
libCudaOptimize: an open source library of GPU-based metaheuristics
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
A comparative study of three GPU-based metaheuristics
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Speeding up model building for ECGA on CUDA platform
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Differential evolution based human body pose estimation from point clouds
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Particle Swarm Optimization and Differential Evolution for model-based object detection
Applied Soft Computing
Credit portfolio management using two-level particle swarm optimization
Information Sciences: an International Journal
Digital Signal Processing
Parallel ant colony optimisation algorithm for continuous domains on graphics processing unit
International Journal of Computing Science and Mathematics
The Journal of Supercomputing
The continuous differential ant-stigmergy algorithm for numerical optimization
Computational Optimization and Applications
A parallel Bees Algorithm implementation on GPU
Journal of Systems Architecture: the EUROMICRO Journal
Solving the k-influence region problem with the GPU
Information Sciences: an International Journal
Hi-index | 0.07 |
Particle swarm optimization (PSO), like other population-based meta-heuristics, is intrinsically parallel and can be effectively implemented on Graphics Processing Units (GPUs), which are, in fact, massively parallel processing architectures. In this paper we discuss possible approaches to parallelizing PSO on graphics hardware within the Compute Unified Device Architecture (CUDA(TM)), a GPU programming environment by nVIDIA(TM) which supports the company's latest cards. In particular, two different ways of exploiting GPU parallelism are explored and evaluated. The execution speed of the two parallel algorithms is compared, on functions which are typically used as benchmarks for PSO, with a standard sequential implementation of PSO (SPSO), as well as with recently published results of other parallel implementations. An in-depth study of the computation efficiency of our parallel algorithms is carried out by assessing speed-up and scale-up with respect to SPSO. Also reported are some results about the optimization effectiveness of the parallel implementations with respect to SPSO, in cases when the parallel versions introduce some possibly significant difference with respect to the sequential version.