Real-Time Incompressible Fluid Simulation on the GPU
We present a parallel framework for simulating incompressible fluids with predictive-corrective incompressible smoothed particle hydrodynamics (PCISPH) on the GPU in real time. To this end, we propose an efficient GPU streaming pipeline to map the entire computational task onto the GPU, fully exploi...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | International Journal of Computer Games Technology |
| Online Access: | http://dx.doi.org/10.1155/2015/417417 |
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| _version_ | 1832562252039847936 |
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| author | Xiao Nie Leiting Chen Tao Xiang |
| author_facet | Xiao Nie Leiting Chen Tao Xiang |
| author_sort | Xiao Nie |
| collection | DOAJ |
| description | We present a parallel framework for simulating incompressible fluids with predictive-corrective incompressible smoothed particle hydrodynamics (PCISPH) on the GPU in real time. To this end, we propose an efficient GPU streaming pipeline to map the entire computational task onto the GPU, fully exploiting the massive computational power of state-of-the-art GPUs. In PCISPH-based simulations, neighbor search is the major performance obstacle because this process is performed several times at each time step. To eliminate this bottleneck, an efficient parallel sorting method for this time-consuming step is introduced. Moreover, we discuss several optimization techniques including using fast on-chip shared memory to avoid global memory bandwidth limitations and thus further improve performance on modern GPU hardware. With our framework, the realism of real-time fluid simulation is significantly improved since our method enforces incompressibility constraint which is typically ignored due to efficiency reason in previous GPU-based SPH methods. The performance results illustrate that our approach can efficiently simulate realistic incompressible fluid in real time and results in a speed-up factor of up to 23 on a high-end NVIDIA GPU in comparison to single-threaded CPU-based implementation. |
| format | Article |
| id | doaj-art-28a89381ab984e8f9fd5471cc103d5a3 |
| institution | Kabale University |
| issn | 1687-7047 1687-7055 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Computer Games Technology |
| spelling | doaj-art-28a89381ab984e8f9fd5471cc103d5a32025-02-03T01:23:01ZengWileyInternational Journal of Computer Games Technology1687-70471687-70552015-01-01201510.1155/2015/417417417417Real-Time Incompressible Fluid Simulation on the GPUXiao Nie0Leiting Chen1Tao Xiang2School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaWe present a parallel framework for simulating incompressible fluids with predictive-corrective incompressible smoothed particle hydrodynamics (PCISPH) on the GPU in real time. To this end, we propose an efficient GPU streaming pipeline to map the entire computational task onto the GPU, fully exploiting the massive computational power of state-of-the-art GPUs. In PCISPH-based simulations, neighbor search is the major performance obstacle because this process is performed several times at each time step. To eliminate this bottleneck, an efficient parallel sorting method for this time-consuming step is introduced. Moreover, we discuss several optimization techniques including using fast on-chip shared memory to avoid global memory bandwidth limitations and thus further improve performance on modern GPU hardware. With our framework, the realism of real-time fluid simulation is significantly improved since our method enforces incompressibility constraint which is typically ignored due to efficiency reason in previous GPU-based SPH methods. The performance results illustrate that our approach can efficiently simulate realistic incompressible fluid in real time and results in a speed-up factor of up to 23 on a high-end NVIDIA GPU in comparison to single-threaded CPU-based implementation.http://dx.doi.org/10.1155/2015/417417 |
| spellingShingle | Xiao Nie Leiting Chen Tao Xiang Real-Time Incompressible Fluid Simulation on the GPU International Journal of Computer Games Technology |
| title | Real-Time Incompressible Fluid Simulation on the GPU |
| title_full | Real-Time Incompressible Fluid Simulation on the GPU |
| title_fullStr | Real-Time Incompressible Fluid Simulation on the GPU |
| title_full_unstemmed | Real-Time Incompressible Fluid Simulation on the GPU |
| title_short | Real-Time Incompressible Fluid Simulation on the GPU |
| title_sort | real time incompressible fluid simulation on the gpu |
| url | http://dx.doi.org/10.1155/2015/417417 |
| work_keys_str_mv | AT xiaonie realtimeincompressiblefluidsimulationonthegpu AT leitingchen realtimeincompressiblefluidsimulationonthegpu AT taoxiang realtimeincompressiblefluidsimulationonthegpu |