{"title":"GPU加速快速有限元变形模拟","authors":"Youquan Liu, Shaohui Jiao, Wen Wu, S. De","doi":"10.1109/APCCAS.2008.4746096","DOIUrl":null,"url":null,"abstract":"In this paper we present a general FEM (finite element method) solution that enables fast dynamic deformation simulation on the newly available GPU (graphics processing unit) hardware with compute unified device architecture (CUDA) from NVIDIA. CUDA-enabled GPUs harness the power of 128 processors which allow data parallel computations. Compared to the previous GPGPU, it is significantly more flexible with a C language interface. We not only implement FEM deformation computation algorithms with CUDA but also analyze the performance in detail. Our test results indicate that the GPU with CUDA enables about 4 times speedup for FEM deformation computation on an Intel(R) Core 2 Quad 2.0 GHz machine with GeForce 8800 GTX.","PeriodicalId":344917,"journal":{"name":"APCCAS 2008 - 2008 IEEE Asia Pacific Conference on Circuits and Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"GPU accelerated fast FEM deformation simulation\",\"authors\":\"Youquan Liu, Shaohui Jiao, Wen Wu, S. De\",\"doi\":\"10.1109/APCCAS.2008.4746096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present a general FEM (finite element method) solution that enables fast dynamic deformation simulation on the newly available GPU (graphics processing unit) hardware with compute unified device architecture (CUDA) from NVIDIA. CUDA-enabled GPUs harness the power of 128 processors which allow data parallel computations. Compared to the previous GPGPU, it is significantly more flexible with a C language interface. We not only implement FEM deformation computation algorithms with CUDA but also analyze the performance in detail. Our test results indicate that the GPU with CUDA enables about 4 times speedup for FEM deformation computation on an Intel(R) Core 2 Quad 2.0 GHz machine with GeForce 8800 GTX.\",\"PeriodicalId\":344917,\"journal\":{\"name\":\"APCCAS 2008 - 2008 IEEE Asia Pacific Conference on Circuits and Systems\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"APCCAS 2008 - 2008 IEEE Asia Pacific Conference on Circuits and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APCCAS.2008.4746096\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"APCCAS 2008 - 2008 IEEE Asia Pacific Conference on Circuits and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCCAS.2008.4746096","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we present a general FEM (finite element method) solution that enables fast dynamic deformation simulation on the newly available GPU (graphics processing unit) hardware with compute unified device architecture (CUDA) from NVIDIA. CUDA-enabled GPUs harness the power of 128 processors which allow data parallel computations. Compared to the previous GPGPU, it is significantly more flexible with a C language interface. We not only implement FEM deformation computation algorithms with CUDA but also analyze the performance in detail. Our test results indicate that the GPU with CUDA enables about 4 times speedup for FEM deformation computation on an Intel(R) Core 2 Quad 2.0 GHz machine with GeForce 8800 GTX.
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