Graphics Hardware Acceleration of Particle Swarm Optimization with Digital Pheromones using the CUDA Architecture

*† Modern GPUs have proven to outperform the number of floating point operations when compared to CPUs through inherent data parallel architecture and higher bandwidth capabilities. The advent of programmable graphics hardware in recent times further provided a suitable platform for scientific computing, particularly in the field of population based optimization algorithms. Previous work by the authors demonstrated the capability of digital pheromones within PSO for searching n-dimensional design spaces with improved accuracy, efficiency and reliability in both serial and parallel CPU computing environments. Preliminary GPU implementations were also made using OpenCL and OpenGL Shading Languge by off-loading objective function evaluations to the GPU. In this paper, hardware acceleration of Particle Swarm Optimization with digital pheromones using the CUDA architecture on commodity Graphics Processing Unit (GPU) is investigated and presented. Specifically, two objectives will be attained in this work: 1) a successful implementation of PSO with digital pheromones on a high-end workstation GPU and a popular low-cost consumer level GPU and 2) results comparison between these implementations. Based on testing the algorithm with a number of unconstrained problems, recommendations will be made on the suitability of high-end or consumer level GPUs for solving population based optimization problems.

[1]  Eric Bonabeau,et al.  Swarm Intelligence: A New C2 Paradigm with an Application to Control Swarms of UAVs , 2003 .

[2]  Tony White,et al.  Towards multi-swarm problem solving in networks , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[3]  Andries Petrus Engelbrecht,et al.  Fundamentals of Computational Swarm Intelligence , 2005 .

[4]  Eliot Winer,et al.  A parallel implementation of particle swarm optimization using digital pheromones , 2006 .

[5]  Nabil H. Mustafa,et al.  Hardware-assisted view-dependent map simplification , 2001, SCG '01.

[6]  V. Pascucci,et al.  Isosurface computation made simple: hardware acceleration, adaptive refinement and tetrahedral stripping , 2004, VISSYM'04.

[7]  Russell C. Eberhart,et al.  Particle swarm with extended memory for multiobjective optimization , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[8]  James H. Oliver,et al.  UAV Swarm Control: Calculating Digital Pheromone Fields with the GPU , 2006 .

[9]  Eliot Winer,et al.  Improving solution characteristics of particle swarm optimization using digital pheromones , 2009 .

[10]  Pedro Trancoso,et al.  Initial Experiences Porting a Bioinformatics Application to a Graphics Processor , 2005, Panhellenic Conference on Informatics.

[11]  B. P. Wang,et al.  Particle Swarm Optimization for Mixed Discrete, Integer and Continuous Variables , 2004 .

[12]  Jaroslaw Sobieszczanski-Sobieski,et al.  Particle swarm optimization , 2002 .

[13]  Hitoshi Iba,et al.  Particle swarm optimization with Gaussian mutation , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[14]  Eliot Winer,et al.  Implementation of digital pheromones in PSO accelerated by commodity Graphics Hardware , 2008 .

[15]  Naga K. Govindaraju,et al.  A Survey of General‐Purpose Computation on Graphics Hardware , 2007 .

[16]  Eliot Winer,et al.  Performance of hardware accelerated particle swarm optimization with digital pheromones on dissimilar computing platforms , 2010 .

[17]  Tamy Boubekeur,et al.  Generic mesh refinement on GPU , 2005, HWWS '05.

[18]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[19]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[20]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[21]  B J Fregly,et al.  Parallel global optimization with the particle swarm algorithm , 2004, International journal for numerical methods in engineering.

[22]  Marco Dorigo,et al.  Distributed Optimization by Ant Colonies , 1992 .

[23]  Russell C. Eberhart,et al.  Swarm intelligence for permutation optimization: a case study of n-queens problem , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[24]  Byung-Il Koh,et al.  Parallel asynchronous particle swarm optimization , 2006, International journal for numerical methods in engineering.

[25]  Yuhui Shi,et al.  Particle swarm optimization: developments, applications and resources , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[26]  H. Van Dyke Parunak,et al.  DIGITAL PHEROMONES FOR AUTONOMOUS COORDINATION OF SWARMING UAV'S , 2002 .

[27]  David Defour,et al.  Implementation of float-float operators on graphics hardware , 2006, ArXiv.

[28]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[29]  Eliot Winer,et al.  A Statistical Analysis of Particle Swarm Optimization With and Without Digital Pheromones , 2007 .

[30]  Nabil H. Mustafa,et al.  Streaming Geometric Optimization Using Graphics Hardware , 2003, ESA.

[31]  J. Sobieszczanski-Sobieski,et al.  Multidisciplinary optimization of a transport aircraft wing using particle swarm optimization , 2004 .

[32]  Geoff Leach,et al.  Improved CSG rendering using overlap graph subtraction sequences , 2003, GRAPHITE '03.

[33]  Xiaohui Hu,et al.  Engineering optimization with particle swarm , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[34]  Jaco F. Schutte,et al.  Particle swarms in sizing and global optimization , 2002 .

[35]  Russell C. Eberhart,et al.  Solving Constrained Nonlinear Optimization Problems with Particle Swarm Optimization , 2002 .

[36]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[37]  Russell C. Eberhart,et al.  Parameter Selection in Particle Swarm Optimization , 1998, Evolutionary Programming.

[38]  Eliot Winer,et al.  Digital Pheromone Implementation of PSO with Velocity Vector Accelerated by Commodity Graphics Hardware , 2006 .