10870

Accelerating a Novel Particle-based Fluid Simulation on the GPU

Zhilu Chen, James Kingsley, Xinming Huang, Erkan Tuzel
Department of Electrical and Computer Engineering, Worcester Polytechnic Institute
IEEE High Performance Extreme Computing Conference(HPEC ’13), 2013

@article{chen2013accelerating,

   title={Accelerating a Novel Particle-based Fluid Simulation on the GPU},

   author={Chen, Zhilu and Kingsley, James and Huang, Xinming and T{"u}zel, Erkan},

   year={2013}

}

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Stochastic Rotation Dynamics (SRD) is a novel particle-based simulation method that can be used to model complex fluids [1], [2], such as binary and ternary mixtures [3], and polymer solutions [4]-[6], in either two or three dimensions. Although SRD is efficient compared to traditional methods, it is still computationally expensive for large system sizes, e.g. when using a large array of particles to simulate dense polymer solutions. Recently, as the power offered by Graphics Processing Units (GPUs) has risen, General Purpose GPU (GPGPU) computing has been introduced as an effective way to improve performance for parallel computation tasks. This work focuses on the acceleration of SRD simulations using Nvidia’s GPGPU architecture, CUDA. We find that while the speed improvements delivered by GPU acceleration vary with the simulation version and parameters used, our GPU implementation runs around 10 times faster than the CPU version for basic simulations, and up to 50 times faster for polymers in solution.
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