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A CUDA-based implementation of an improved SPH method on GPU
DOI:10.1016/j.amc.2020.125482.png)
摘要
En 中文
We present a CUDA-based parallel implementation on GPU architecture of a modified version of the Smoothed Particle Hydrodynamics (SPH) method. This modified formulation exploits a strategy based on the Taylor series expansion, which simultaneously improves the approximation of a function and its derivatives with respect to the standard formulation. The improvement in accuracy comes at the cost of an additional computational effort. The computational demand becomes increasingly crucial as problem size increases but can be addressed by employing fast summations in a parallel computational scheme. The experimental analysis showed that our parallel implementation significantly reduces the runtime, when compared to the CPU-based implementation. (C) 2020 Elsevier Inc. All rights reserved.
Keyword:
Smoothed particle hydrodynamics
Fast gauss transform
Graphics processing unit
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期刊
IF:
3.4
论文数:
2.3W
被引数:
3.3W
机构
引用论文
Optimization of parameters for semiempirical methods VI: more modifications to the NDDO approximations and re-optimization of parameters半经验方法的参数优化VI: 对NDDO近似值的更多修改和参数的重新优化
Smoothed particle hydrodynamics: theory and application to non-spherical stars光滑粒子流体动力学: 非球形恒星的理论和应用

