{"title":"fpga加速粒子胞内等离子体模拟的高效粒子网格空间插值","authors":"Almomany Abedalmuhdi, B. Wells, K. Nishikawa","doi":"10.1109/FCCM.2017.63","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":124631,"journal":{"name":"2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Efficient Particle-Grid Space Interpolation of an FPGA-Accelerated Particle-in-Cell Plasma Simulation\",\"authors\":\"Almomany Abedalmuhdi, B. Wells, K. Nishikawa\",\"doi\":\"10.1109/FCCM.2017.63\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":124631,\"journal\":{\"name\":\"2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FCCM.2017.63\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FCCM.2017.63","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient Particle-Grid Space Interpolation of an FPGA-Accelerated Particle-in-Cell Plasma Simulation
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.