GPU acceleration of Eulerian–Lagrangian particle-laden turbulent flow simulations. (February 2018)

• Record Type: Journal Article
• Authors: Sweet, James; Richter, David H.; Thain, Douglas
• Is Part Of: International journal of multiphase flow. Volume 99(2018)
• Page Start: 437
• Page End: 445
• Publication Date: 2018-02
• Subjects: Graphics processing unit -- Particle-laden turbulent flow simulation; Multiphase flow -- Periodicals; Écoulement polyphasique -- Périodiques; Multiphase flow; Periodicals; 620.1064
• DOI: 10.1016/j.ijmultiphaseflow.2017.11.010
• Languages: English
• ISSNs: 0301-9322

Abstract

Highlights: Acceleration of up to 14x can be achieved by performing Lagrangian particle computations on GPU hardware. Affordable multiscale time integration is made possible through usage of GPU. Abstract: Acceleration of an existing MPI-based, particle-laden turbulent flow simulation code is achieved using up to four NVIDIA GPU devices. The overall design is to transfer the entire flow velocity, temperature, and humidity fields to each device, and compute particle trajectories entirely on the GPU hardware. For one-way coupled turbulent flow simulations, accurate simulations can be achieved for less computational cost than the original CPU implementation for particle numbers above 10 6 . Above 10 7 particles, the GPU version is roughly 14 times faster than the original CPU implementation. The effects of interpolation order, precision of the transferred Eulerian fields, and sub-time-stepping for fast particle dynamics are discussed.