Swarm intelligence algorithm an overview sciencedirect topics. Buy gpu based parallel implementation of swarm intelligence algorithms at. Read gpu based parallel implementation of swarm intelligence algorithms by ying tan available from rakuten kobo. Gpubased parallel implementation of swarm intelligence algorithms provides guidance on the appropriate implementation of swarm intelligence algorithms on the gpu platform after describing gpgpu in a concise way. Performance evaluation of particle swarm optimization. Benchmark function an overview sciencedirect topics. Gpu based parallel implementation of swarm intelligence algorithms. This paper presents a good implementation for the standard particle swarm optimization spso on a gpu based on the cuda architecture, which uses. Gpufwa modifies the original fwa to suit the particular architecture of the gpu.
Sahingoz proposed, a uav path planning with parallel aco algorithm on cuda platform. The ant colony optimization algorithm for endmember extraction acoee, a representative endmember extraction method based on swarm intelligence algorithms, utilizes artificial ants to imitate the. Particle swarm optimization pso is a populationbased stochastic search technique for solving. Third international conference on intelligent computing, icic 2007, qingdao, chi. Read graphics processing unit books like gpu based parallel implementation of swarm intelligence algorithms and cuda application design and development for free with a free 30day trial. This book not only presents gpgpu in adequate detail, but also includes guidance on the. Various gpu based implementations from lowlevel rendering languages 16 to lately highlevel general languages 17, 3, 6, 14 have been reported. So far, fwa has been applied for solving practical optimization problems, combined with other optimization algorithms, improved versions, multiobjective fireworks algorithm and parallel implementation. The application of swarm principles to robots is called swarm robotics, while swarm intelligence refers to the more general set of algorithms.
Accelerating swarm intelligence algorithms with gpucomputing. Fireworks algorithm a novel swarm intelligence optimization method. Critical concerns for the efficient parallel implementation of sias are also described in detail. The main objective of this paper is to implement a parallel asynchronous version and synchronous versions of pso on the graphical processing.
Gpubased asynchronous global optimization with particle swarm. Gpubased swarm intelligence for association rule mining. This phenomenon found in nature is the inspiration for swarm intelligence algorithmssystems that utilize the emergent patterns found in natural swarms to solve computational problems. Nine benchmark functions were implemented on the gpu with float numbers of single precision. This book not only presents gpgpu in adequate detail, but also includes guidance on the appropriate implementation of swarm intelligence algorithms on the gpu platform.
This book is devoted to the stateoftheart in all aspects of fireworks algorithm fwa, with particular emphasis on the efficient improved versions of fwa. Various gpubased implementations from lowlevel rendering languages 16 to lately highlevel general languages 17, 3, 6, 14 have been reported. Pure bitmap implementation and tbi trie bitmap implementation. A gpubased parallel fireworks algorithm for optimization. All these functions are minimizing problems while f 1 f 3 are unimodal function while the left are multimodal functions. A novel gpubased parallel implementation scheme and performance analysis of robot forward dynamics algorithms yajue yang, yuanqing wu and jia pan abstractwe propose a novel unifying scheme for parallel implementation of articulated robot dynamics algorithms. With contributions from an international selection of leading researchers, swarm intelligence is essential reading for engineers, researchers, professionals and practitioners with interests in swarm intelligence. Tan and others published a survey on gpu based implementation of swarm intelligence algorithms find, read and cite all the research you need on researchgate. Parallelization of enhanced firework algorithm using. Parallel implementation of particle swarm optimization variants using graphics. A novel swarm intelligence optimization method ying tan auth. Ying tan, in gpu based parallel implementation of swarm intelligence algorithms, 2016. Recent work has involved merging the global search properties of sds with other swarm intelligence algorithms.
Examples of swarm intelligence in natural systems include ant colonies, bird flocking, hawks hunting, animal herding, bacterial growth, fish schooling and microbial intelligence. It solves a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the searchspace according to simple mathematical formulae. Swarm intelligence algorithm an overview sciencedirect. One of the swarm intelligence algorithms advantages is the relative ease of the software implementation, which ensues from the basic principle of simple movement rules of individual agents. Gpu based parallel implementation of swarm intelligence algorithms ying tan on. These approaches have been adapted for solving the arm problem in the psoarm, r, penguins search optimization and bsoarm algorithms, to name a few. Swarm intelligence algorithms have been widely used to solve difficult real world problems in both academic and engineering domains. This book not only presents gpgpu in adequate detail, but also includes guidance on the appropriate implementation of swarm intelligence algorithms.
In this paper we adopt the generalpurpose gpu parallel computing model and show how it can be leveraged to increase the accuracy and e. Parallel particle swarm optimization approaches on. Multiswarm pso algorithm for the quadratic assignment. Csps are the focus of many artificial intelligence applications and operational researches, such as resources. This book synthesizes material that has previously only been available in primary literature. Parallel implementation swarm for sale elsa frozen ii. Fireworks algorithm fwa is a recently proposed swarm. Parallel global optimization with the particle swarm algorithm. In this paper, we will show that due to their implicitly parallel structure, swarm intelligence algorithms of all sorts can benefit from gpubased implementations. Three alternatives for parallel gpubased implementations of. Implementation of popular swarm intelligence models. A survey on gpu based implementation of swarm intelligence algorithms orcid0000000182434731 article pdf available in ieee transactions on cybernetics 469.
Learn from graphics processing unit experts like ying tan and rob farber. Gpubased parallel implementation of swarm intelligence algorithms combines and covers two emerging areas attracting increased attention and applications. Gpubased parallel particle swarm optimization methods for graph. A survey on gpubased implementation of swarm intelligence algorithms orcid0000000182434731 article pdf available in ieee transactions on cybernetics 469.
Adaptive particle swarm optimization apso features better search efficiency than standard pso. Multiagent algorithm for finding multiple noisy radiation. Sensors free fulltext multigpu based parallel design of. Pdf a survey on gpubased implementation of swarm intelligence. The companion volume 2 covers innovations, new algorithms and methods, and volume 3 covers applications of swarm intelligence algorithms. Fireworks algorithm a novel swarm intelligence optimization. Gpu based parallel implementation of swarm intelligence algorithms by tan new. Gpu based parallel implementation of swarm intelligence algorithms combines and covers two emerging areas attracting increased attention and applications.
In sequels, several successful applications of fwa on nonnegative matrix factorization nmf, text clustering, pattern recognition, and seismic inversion problem, and swarm robotics, are illustrated in details, which might shed new light on more realworld applications in future. Moreover, novel criteria are also proposed to evaluate and compare the parallel implementation and algorithm performance universally. By using the generalpurpose computing ability of gpu and based on the software platform of. Ying tan, in gpubased parallel implementation of swarm intelligence algorithms, 2016.
Gpubased parallel particle swarm optimization you zhou, and ying tan, senior member, ieee abstracta novel parallel approach to run standard particle swarm optimization spso on graphic processing unit gpu is presented in this paper. Gpu based parallel implementation of swarm intelligence algorithms combines and covers two emerging areas attracting inc. Hence, these algorithms lend themselves well to parallel implementations thereby speeding up the optimization process. Mvsa 9, and some other new algorithms proposed recently 10. Multi swarm optimization is a variant of particle swarm optimization pso based on the use of multiple subswarms instead of one standard swarm. Furthermore, the performances of cpubased and gpu based algorithms are. A survey on gpu based implementation of swarm intelligence algorithms ying tan, senior member, ieee, and ke ding abstractinspired by the collective behavior of natural swarm, swarm intelligence algorithms sias have been developed and widely used for solving optimization problems. General purpose computing on the gpu3 parallel models4 performance measurements5 implementation considerations6 gpu based particle swarm optimization7 gpu based fireworks algorithm 8 attractrepulse fireworks algorithm using dynamic parallelism9 other typical swarm intelligence algorithms based on gpus10. Gpubased parallel implementation of swarm intelligence. Since the introduction of fwa, it has attracted the attentions from the researchers to develop the conversion algorithm.
Ying tan gpu based parallel implementation of swarm intelligence algorithms combines and covers two emerging areas attracting increased attention and applications. Swarm intelligence algorithms, similarly to any populationbased metaheuristics, are composed of three steps. Pso has become popular due to its simplicity and its effectiveness in wide range of application with low computational cost. Our purpose is to implement a pso based method by using. Fireworks algorithm fwa is a novel swarm intelligence algorithm under active research 184, 181, 180. Bin yang, kaiuwe bletzinger, qilin zhang and zhihao zhou, frame structural sizing and topological optimization via a parallel implementation of a modified particle swarm algorithm, ksce journal of civil engineering, 17, 6, 59, 20. A novel gpubased parallel implementation scheme and. Pbi represents transactions and itemsets using a bitmap. Content is final as presented, with the exception of pagination. Mar 31, 2020 pdf fireworks algorithm by ying tan, algorithms.
All the algorithms are tested on the benchmark instances to demonstrate their efficacy and effectiveness. Discover the best graphics processing unit books and audiobooks. A graph drawing is a pictorial representation of the vertices and edges of a graph. The experiments demonstrated that the processing time of acoee was signi. Additional details of the gpu implementation of pso are found in 17. Inspired by the collective behavior of natural swarm, swarm intelligence algorithms sias have been developed and widely used for solving optimization problems. Apso can perform global search over the entire search space with a higher convergence speed. Swarm intelligence algorithms in artificial intelligence were newly introduced for endmember extraction from hyperspectral images 14,15,16,17,18. Swarm intelligence algorithms for data clustering ajith abraham1, swagatam das2, and sandip roy3 1 center of excellence for quanti. It covers exhaustively the key recent significant research into the improvements of fwa so far. Parallelization of enhanced firework algorithm using mapreduce.
A survey on gpubased implementation of swarm intelligence algorithms ying tan, senior member, ieee, and ke ding abstractinspired by the collective behavior of natural swarm, swarm intelligence algorithms sias have been developed and widely used for solving optimization problems. Thanks to the inherent parallelism, various parallelized swarm intelligence algorithms have been proposed to speed up the optimization process, especially on the massively parallel processing architecture gpus. The general approach in multi swarm optimization is that. Gpubased parallel implementation of swarm intelligence algorithms. Tan and others published a survey on gpubased implementation of swarm intelligence algorithms find, read and cite all the research you need on researchgate. Particle swarm optimization pso is a population based stochastic search technique for solving optimization problems, which has been proven to be effective in a wide range of applications. Ieee transactions on cybernetics 1 a survey on gpu based implementation of swarm intelligence algorithms, year. In computational science, particle swarm optimization pso is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. In sequels, several successful applications of fwa on nonnegative matrix factorization nmf, text clustering. A survey on parallel particle swarm optimization algorithms. Gpubased parallel particle swarm optimization methods for. Gpubased swarm intelligence for association rule mining in.
Advanced intelligent computing theories and applications. A gpubased implementation, obviously, does not change the general properties of the algorithms. Gpu based swarm intelligence for association rule mining in big databases article type. Features of hardware implementation of particle swarm. In this paper we compare gpubased implementations of three metaheuristics. In particular, we focus on the implementation of two parallel novel. In addition, the book describes a few advanced topics in the research of fwa, including multiobjective optimization moo, discrete fwa dfwa for combinatorial optimization, and gpu based fwa for parallel implementation. Therefore, most of the swarm algorithms implementations are software. However, the computational efficiency on largescale problems is still unsatisfactory. A survey on gpu based implementation of swarm intelligence algorithms. Gpubased parallel implementation of swarm intelligence algorithms 1st edition isbn. Gpufwa modifies the original fwa to suit the particular.
Particle swarm optimization pso may be easy but powerful optimization algorithm relying on the social behavior of the particles. A simple version and a revised version of gpu based mmas are proposed and implemented on the cuda platform. Citeseerx this article has been accepted for inclusion. A survey on gpubased implementation of swarm intelligence.
Without the need for a tradeoff between convergence exploitation and divergence exploration, an adaptive mechanism can be introduced. This paper describes our latest implementation of particle swarm optimization pso with simple ring topology for modern graphic processing units gpus. Particle swarm optimization pso is a populationbased stochastic search technique for solving optimization problems, which has been proven to be effective in a wide range of applications. A survey on gpu based implementation of swarm intelligence algorithms abstract. Swarm intelligence algorithms are inherently parallel since different individuals in the swarm perform independent computations at different positions simultaneously. As well, we give for granted that gpubased implementation of both algorithm and. A comparative study of three gpubased metaheuristics. While highlighting topics such as convergence rate, parameter applications, and global optimization analysis, this publication explores uptodate progress on the specific techniques of this algorithmprovided by publisher handbook of research on fireworks algorithms and swarm intelligence can improve the readers memory. In this chapter, a very efficient fwa variant based on graphics processing units gpus, called gpufwa for short, is introduced 49.
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