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GPU Enabled Particle Swarm Optimization

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Killada, Bala Venkata Rama Kishore
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GPU Enabled Particle Swarm Optimization (1.572Mb)
Abstract
GPUs are massively parallelized devices. They were designed to handle billions of pixels per second. It is does this by embracing an incredible level of parallelism. GPUs in fact can leverage any other parallel algorithms developed for super computers. Many disciplines in science and engineering are achieving high speedups on their codes using GPUs. This paper implements a GPU-enabled Particle Swarm Optimization (PSO) algorithm and evaluates the scalability of the algorithm. Several experiments were conducted comparing the CPU with the GPU implementation, analyzing the scalability of the GPU implementation with regards to increases in population size and dimension, as well as memory usage needed. Overall, the results reveal that the GPU implementation of the PSO algorithm scales very well executed on the Nvidia Tesla K40.
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http://hdl.handle.net/10365/25950
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  • Computer Science Masters Papers

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Student Focused, Land Grant, Research Institution

  • Campus Map
    • Campus Map (pdf)
    • Building list
    • Campus Offices
  • Equity
  • Employment
  • Phone/Email Directory
  • Online Services
    • Blackboard
    • One Stop
    • Campus Connection
    • IT Help Desk
    • Libraries
    • Email
    • Student Success Collaborative
  • Registration And Records
    • Course Schedule
    • Dates and Deadlines
North Dakota State University - Libraries
Circulation: (701) 231-8888 | Reference: (701) 231-8886
Administration: (701) 231-8753
Main Library address: 1201 Albrecht Boulevard
Mailing address: Dept #2080 PO Box 6050, Fargo, ND 58108-6050
Site manager: Site manager
Contact Us |