A CUDA-Based Cooperative Evolutionary Multi-Swarm Optimization Applied to Engineering Problems

Daniel Leal Souza, Otavio Noura Teixeira, Dionne Monteiro, Roberto Celio Limao de Oliveira
Laboratory of Natural Computing (LCN), Area of Exact and Natural Sciences (ACET), University Centre of Para (CESUPA), Belem, Brazil
CSBC, 2012

   title={A CUDA-Based Cooperative Evolutionary Multi-Swarm Optimization Applied to Engineering Problems},

   author={Souza, Daniel Leal and Roberto, Ot{‘a}vio Noura Teixeira1 Dionne Monteiro and de Oliveira, C{‘e}lio Lim{~a}o},



Download Download (PDF)   View View   Source Source   



This paper presents a variation of Evolutionary Particle Swarm Optimization applied to the concept of master/slave swarm with mechanism of sharing data for the acceleration of convergence. The implementation called Cooperative Evolutionary MultiSwarm Optimization on Graphics Processing Units (CMEPSOGPU) consists in using thousands of threads in various slave swarms on the CUDA parallel architecture, where each one works in a parallel and cooperative way in order to improve the search for best result and reduce the number of iterations. The use of CMEPSO-GPU applied to engineering problems showed superior results when compared to other implementations found in the scientific literature.
VN:F [1.9.22_1171]
Rating: 5.0/5 (1 vote cast)
A CUDA-Based Cooperative Evolutionary Multi-Swarm Optimization Applied to Engineering Problems, 5.0 out of 5 based on 1 rating

* * *

* * *

Like us on Facebook

HGPU group

237 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1439 peoples are following HGPU @twitter

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2015 hgpu.org

All rights belong to the respective authors

Contact us: