Fast neighbor search on GPU for Ghost SPH simulation
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摘要: 提出了一種全新的快速鄰居搜索方法,該方法可提高基于光滑粒子動力學的流體模擬在圖形處理器上的運行效率.此外,這種新的鄰居表建立方法可以對兩種或者兩種以上的粒子進行鄰居搜索,使所有粒子能在同一背景網格下擁有獨立的粒子屬性.在此基礎上,引入了Ghost邊界粒子以加強光滑粒子動力學方法在邊界模擬上的準確性,從而使流體模擬更加真實.實驗證明,與傳統的基于圖形處理器的光滑粒子動力學模擬相比,本文方法效率更高.Abstract: This paper presents a novel fast neighbor searching method. By using this method,fluid simulation based on smooth particle hydrodynamics(SPH) can be parallelized easily and run on graphic processing unit(GPU) with high efficiency. The neighbor searching method can search two or more kinds of particles,while saving their information in the same background grid. Ghost boundary particles are introduced to improve the accuracy of boundaries,which can enhance the fidelity of the fluid simulation. Experiments show that the proposed method is more efficient than the traditional SPH method based on GPU.
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