GPU Acceleration of the Generalized Interpolation Material Point Method

نویسندگان

  • Wei-Fan Chiang
  • Michael DeLisi
  • Todd Hummel
  • Tyler Prete
  • Kevin Tew
  • Mary Hall
چکیده

This paper describes our experience rewriting a sequential particle-in-cell code so that its key computations are executed on a GPU. This code is well-suited to GPU acceleration, as it performs data-parallel operations on a regular grid. Key performance challenges are the need for global synchronization in mapping particles to grid nodes, and managing memory bandwidth to global memory. Performance results show overall speedups of 3.3x including the time to display the results of simulation, or 10.9x without the display I/O overhead. Keywords-component; Particle-in-cell code, GPU acceleration

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تاریخ انتشار 2009