A survey on gpu based implementation of swarm intelligence algorithms abstract. Pbi represents transactions and itemsets using a bitmap. Parallel implementation swarm for sale elsa frozen ii. Swarm intelligence algorithms have been widely used to solve difficult real world problems in both academic and engineering domains. Although gpus have been successful in accelerating swarm intelligence algorithms, conventional swarm intelligence algorithms are usually designed to be used under small swarm size. By using the generalpurpose computing ability of gpu and based on the software platform of. Swarm intelligence algorithms in artificial intelligence were newly introduced for endmember extraction from hyperspectral images 14,15,16,17,18. A simple version and a revised version of gpu based mmas are proposed and implemented on the cuda platform. Ying tan gpu based parallel implementation of swarm intelligence algorithms combines and covers two emerging areas attracting increased attention and applications. 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. Therefore, most of the swarm algorithms implementations are software. Citeseerx this article has been accepted for inclusion. As well, we give for granted that gpubased implementation of both algorithm and. Inspired by the collective behavior of natural swarm, swarm intelligence algorithms sias have been developed and widely used for solving optimization problems.
Sahingoz proposed, a uav path planning with parallel aco algorithm on cuda platform. Parallel global optimization with the particle swarm algorithm. Gpubased swarm intelligence for association rule mining in. 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. Parallel particle swarm optimization approaches on. Hence, these algorithms lend themselves well to parallel implementations thereby speeding up the optimization process. Gpu based parallel implementation of swarm intelligence algorithms combines and covers two emerging areas attracting increased attention and applications. A comparative study of three gpubased metaheuristics. In this paper we adopt the generalpurpose gpu parallel computing model and show how it can be leveraged to increase the accuracy and e. 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 appropriate implementation of swarm intelligence algorithms. A graph drawing is a pictorial representation of the vertices and edges of a graph. Performance evaluation of particle swarm optimization.
Swarm intelligence algorithm an overview sciencedirect topics. 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. 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. Advanced intelligent computing theories and applications. 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. The general approach in multi swarm optimization is that. 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.
Recent work has involved merging the global search properties of sds with other swarm intelligence algorithms. So far, fwa has been applied for solving practical optimization problems, combined with other optimization algorithms, improved versions, multiobjective fireworks algorithm and parallel implementation. Furthermore, the performances of cpubased and gpu based algorithms are. 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. Gpu based parallel implementation of swarm intelligence algorithms. Gpu based swarm intelligence for association rule mining in big databases article type. 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. 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. The main objective of this paper is to implement a parallel asynchronous version and synchronous versions of pso on the graphical processing.
In particular, we focus on the implementation of two parallel novel. A survey on gpu based implementation of swarm intelligence algorithms orcid0000000182434731 article pdf available in ieee transactions on cybernetics 469. These approaches have been adapted for solving the arm problem in the psoarm, r, penguins search optimization and bsoarm algorithms, to name a few. Adaptive particle swarm optimization apso features better search efficiency than standard pso. Gpubased parallel implementation of swarm intelligence algorithms combines and covers two emerging areas attracting increased attention and applications. 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 gpubased implementation of swarm intelligence. Fireworks algorithm fwa is a recently proposed swarm. Gpu based parallel implementation of swarm intelligence algorithms ying tan on. Apso can perform global search over the entire search space with a higher convergence speed.
Accelerating swarm intelligence algorithms with gpucomputing. Gpubased 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. Examples of swarm intelligence in natural systems include ant colonies, bird flocking, hawks hunting, animal herding, bacterial growth, fish schooling and microbial intelligence. Moreover, novel criteria are also proposed to evaluate and compare the parallel implementation and algorithm performance universally. In this chapter, a very efficient fwa variant based on graphics processing units gpus, called gpufwa for short, is introduced 49. Ying tan, in gpu based parallel implementation of swarm intelligence algorithms, 2016. Swarm intelligence algorithms are inherently parallel since different individuals in the swarm perform independent computations at different positions simultaneously. Fireworks algorithm a novel swarm intelligence optimization method. 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. The experiments demonstrated that the processing time of acoee was signi. Pure bitmap implementation and tbi trie bitmap implementation.
Multiagent algorithm for finding multiple noisy radiation. Mvsa 9, and some other new algorithms proposed recently 10. Gpufwa modifies the original fwa to suit the particular. All these functions are minimizing problems while f 1 f 3 are unimodal function while the left are multimodal functions. Swarm intelligence algorithms, similarly to any populationbased metaheuristics, are composed of three steps. A survey on gpu based implementation of swarm intelligence algorithms. Features of hardware implementation of particle swarm.
Various gpu based implementations from lowlevel rendering languages 16 to lately highlevel general languages 17, 3, 6, 14 have been reported. Pdf a survey on gpubased implementation of swarm intelligence. 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. 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. A gpubased implementation, obviously, does not change the general properties of the algorithms. Sensors free fulltext multigpu based parallel design of. Our purpose is to implement a pso based method by using. Learn from graphics processing unit experts like ying tan and rob farber. 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. Particle swarm optimization pso may be easy but powerful optimization algorithm relying on the social behavior of the particles. A survey on gpubased implementation of swarm intelligence algorithms orcid0000000182434731 article pdf available in ieee transactions on cybernetics 469. Pso has become popular due to its simplicity and its effectiveness in wide range of application with low computational cost. 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.
Discover the best graphics processing unit books and audiobooks. 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. Fireworks algorithm a novel swarm intelligence optimization. Buy gpu based parallel implementation of swarm intelligence algorithms at. This paper describes our latest implementation of particle swarm optimization pso with simple ring topology for modern graphic processing units gpus. Mar 31, 2020 pdf fireworks algorithm by ying tan, algorithms. A gpubased parallel fireworks algorithm for optimization. Third international conference on intelligent computing, icic 2007, qingdao, chi. Implementation of popular swarm intelligence models. Nine benchmark functions were implemented on the gpu with float numbers of single precision. Gpufwa modifies the original fwa to suit the particular architecture of the gpu.
Gpu based parallel implementation of swarm intelligence algorithms combines and covers two emerging areas attracting inc. The application of swarm principles to robots is called swarm robotics, while swarm intelligence refers to the more general set of algorithms. This book not only presents gpgpu in adequate detail, but also includes guidance on the. The companion volume 2 covers innovations, new algorithms and methods, and volume 3 covers applications of swarm intelligence algorithms. Ieee transactions on cybernetics 1 a survey on gpu based implementation of swarm intelligence algorithms, year. Parallel implementation of particle swarm optimization variants using graphics. Csps are the focus of many artificial intelligence applications and operational researches, such as resources. 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. Additional details of the gpu implementation of pso are found in 17.
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. 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. Benchmark function an overview sciencedirect topics. All the algorithms are tested on the benchmark instances to demonstrate their efficacy and effectiveness. Gpu based parallel implementation of swarm intelligence algorithms by tan new. It covers exhaustively the key recent significant research into the improvements of fwa so far.
The path is assembled for broadcasted keys and collecting data from a wireless sensor network. However, the computational efficiency on largescale problems is still unsatisfactory. Ying tan, in gpubased parallel implementation of swarm intelligence algorithms, 2016. Fireworks algorithm fwa is a novel swarm intelligence algorithm under active research 184, 181, 180. 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. Three alternatives for parallel gpubased implementations of. Swarm intelligence algorithms for data clustering ajith abraham1, swagatam das2, and sandip roy3 1 center of excellence for quanti. Multi swarm optimization is a variant of particle swarm optimization pso based on the use of multiple subswarms instead of one standard swarm. Particle swarm optimization pso is a populationbased stochastic search technique for solving. This book synthesizes material that has previously only been available in primary literature. Parallelization of enhanced firework algorithm using. Multiswarm pso algorithm for the quadratic assignment.
A novel gpubased parallel implementation scheme and. Content is final as presented, with the exception of pagination. Various gpubased implementations from lowlevel rendering languages 16 to lately highlevel general languages 17, 3, 6, 14 have been reported. 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. Gpubased swarm intelligence for association rule mining. Since the introduction of fwa, it has attracted the attentions from the researchers to develop the conversion algorithm. Gpubased asynchronous global optimization with particle swarm.
A novel swarm intelligence optimization method ying tan auth. In this paper, we will show that due to their implicitly parallel structure, swarm intelligence algorithms of all sorts can benefit from gpubased implementations. This book is devoted to the stateoftheart in all aspects of fireworks algorithm fwa, with particular emphasis on the efficient improved versions of fwa. Critical concerns for the efficient parallel implementation of sias are also described in detail. Parallelization of enhanced firework algorithm using mapreduce. A survey on parallel particle swarm optimization algorithms. Gpubased parallel implementation of swarm intelligence.
Read gpu based parallel implementation of swarm intelligence algorithms by ying tan available from rakuten kobo. In sequels, several successful applications of fwa on nonnegative matrix factorization nmf, text clustering. In this paper we compare gpubased implementations of three metaheuristics. Gpubased parallel implementation of swarm intelligence algorithms 1st edition isbn. Gpubased parallel particle swarm optimization methods for. Gpubased parallel particle swarm optimization methods for graph.
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