Application of High Performance Parallel Computing Based on GPU

Liu Yang; Tie Ying Liu

doi:10.4028/www.scientific.net/AMM.411-414.585

Paper Titles

Performance Analysis of Different Refrigerants in Two Stage Compression Cycle with an Expander
p.568

Design and Implementation of the Universal Database Query Middleware Based on Web Services
p.572

Research of Business Process Intelligent Building and Optimization Platform Base on SOA
p.576

Study on ASP-Based Anti-Spam Management System
p.581

Application of High Performance Parallel Computing Based on GPU
p.585

Research on Web Dynamic Ontology Construction Based on Concept Lattice
p.589

Research and Design on an Improved TOTP Authentication
p.595

Design and Realization of Network Security Defense Architecture of Medical Information Integration Platform
p.600

Detecting Application-Layer Attacks Based on User's Application-Layer Behaviors
p.607

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 411-414Application of High Performance Parallel Computing...

Application of High Performance Parallel Computing Based on GPU

Abstract:

This paper introduces parallel feature of the GPU, which will help GPU parallel computation methods to achieve the parallelization of PSO parallel path search process; and reduce the increasingly high problem of PSO (PSO: Particle Swarm Optimization) in time and space complexity. The experimental results show: comparing with CPU mode, GPU platform calculation improves the search rate and shortens the calculation time.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 411-414)

Pages:

585-588

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.411-414.585

Citation:

Cite this paper

Online since:

September 2013

Authors:

Liu Yang, Tie Ying Liu

Keywords:

CPU, Graphic Processing Unit (GPU), Particle Swarm Optimization (PSO)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Macedonia M.: The GPU Enters Computing's Mainstream Computer. Michael Macedonia, 2003, 36(10): 106~108.

DOI: 10.1109/mc.2003.1236476

Google Scholar

[2] Nadathur Satis. International Parallel and Distributed Processing Symposium, May 2009, 23(2) 655-660.

Google Scholar

[3] G. Karypis and V. Kumar: Transactions on Parallel and Distributed Systems, 1994, 28(5): 453-462.

Google Scholar

[4] M.G. Brockington：International Congress and Convention Association Journal, 1996, 19(3): 162-174.

Google Scholar

[5] Wang Ling: Swarm Intelligence Algorithm and its Application. Beijing：Tsinghua University Press, (2001).

Google Scholar

[6] Shigenori N and Takamu G: Transactions on Power Systems, 2003, 18: 60-68.

Google Scholar

[7] LI Yan-jun and WU Tie-jun. Acta Auomatica Sinica, 2003, 29 (1): 95-101.

Google Scholar

[8] Dorigo M and Maniezzo V: Transactions on SMC, 1996, Part B, 26 (1): 1-13.

Google Scholar

[9] Eberhart RC and Kennedy J: A New Optimizer Using Particle Swarm Theory. Proceedings of the Sixth International Symposium on Micro Machine and Human Science. Service Center. Japan: Nagoya, 1995: 39-43.

DOI: 10.1109/mhs.1995.494215

Google Scholar

[10] Neuwald AF and LiuJ. S, Lwarence C. E: ProteinScience, 1995, 4(8): 1618-16.

Google Scholar