Efficient Particle-Grid Space Interpolation of an FPGA-Accelerated Particle-in-Cell Plasma Simulation

被引:8
作者
Abedalmuhdi, Almomany [1 ]
Wells, B. Earl [1 ]
Nishikawa, Ken-Ichi [2 ]
机构
[1] Univ Alabama, Dept Elect & Comp Engn, Huntsville, AL 35899 USA
[2] Univ Alabama, Dept Phys, Huntsville, AL 35899 USA
来源
2017 IEEE 25TH ANNUAL INTERNATIONAL SYMPOSIUM ON FIELD-PROGRAMMABLE CUSTOM COMPUTING MACHINES (FCCM 2017) | 2017年
关键词
D O I
10.1109/FCCM.2017.63
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This paper highlights on-going research to effectively utilize a commercially available spatially reconfigurable platform and the OpenCL framework to improve the run-time performance and reduce the overall energy consumption of an existing 2.5D Electrostatic Particle-in-Cell type plasma simulation. This problem is constrained by the finite internal FPGA resources and the performance mandate that all main OpenCL kernels for this application reside in a single FPGA image. The paper focuses on solving the particle-to-grid space interpolation phase of the simulation because of its inherent nondeterministic global memory access pattern. The implementation that is presented adheres closely to the original CPU-based model while employing local memory, task level pipelining, and replication of kernel resources to provide a much more deterministic and coalesced access pattern. The overall simulation has been shown to have an approximately 2.5-fold improvement in performance and a eight-fold improvement in energy consumption over the life of the simulation when compared to the reference single core CPU implementation.
引用
收藏
页码:76 / 79
页数:4
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