7,833 research outputs found
Particle-resolved thermal lattice Boltzmann simulation using OpenACC on multi-GPUs
We utilize the Open Accelerator (OpenACC) approach for graphics processing
unit (GPU) accelerated particle-resolved thermal lattice Boltzmann (LB)
simulation. We adopt the momentum-exchange method to calculate fluid-particle
interactions to preserve the simplicity of the LB method. To address load
imbalance issues, we extend the indirect addressing method to collect
fluid-particle link information at each timestep and store indices of
fluid-particle link in a fixed index array. We simulate the sedimentation of
4,800 hot particles in cold fluids with a domain size of , and the
simulation achieves 1750 million lattice updates per second (MLUPS) on a single
GPU. Furthermore, we implement a hybrid OpenACC and message passing interface
(MPI) approach for multi-GPU accelerated simulation. This approach incorporates
four optimization strategies, including building domain lists, utilizing
request-answer communication, overlapping communications with computations, and
executing computation tasks concurrently. By reducing data communication
between GPUs, hiding communication latency through overlapping computation, and
increasing the utilization of GPU resources, we achieve improved performance,
reaching 10846 MLUPS using 8 GPUs. Our results demonstrate that the
OpenACC-based GPU acceleration is promising for particle-resolved thermal
lattice Boltzmann simulation.Comment: 45 pages, 18 figure
A hybrid fluid simulation on the Graphics Processing Unit (GPU)
This thesis presents a method to implement a hybrid particle/grid
uid simulation
on graphics hardware. The goal is to speed up the simulation by exploiting
the parallelism of the graphics processing unit, or GPU. The Fluid Implicit Particle
method is adapted to the programming style of the GPU. The methods were implemented
on a current generation graphics card. The GPU based program exhibited a
small speedup over its CPU based counterpart
A GPU-accelerated package for simulation of flow in nanoporous source rocks with many-body dissipative particle dynamics
Mesoscopic simulations of hydrocarbon flow in source shales are challenging,
in part due to the heterogeneous shale pores with sizes ranging from a few
nanometers to a few micrometers. Additionally, the sub-continuum fluid-fluid
and fluid-solid interactions in nano- to micro-scale shale pores, which are
physically and chemically sophisticated, must be captured. To address those
challenges, we present a GPU-accelerated package for simulation of flow in
nano- to micro-pore networks with a many-body dissipative particle dynamics
(mDPD) mesoscale model. Based on a fully distributed parallel paradigm, the
code offloads all intensive workloads on GPUs. Other advancements, such as
smart particle packing and no-slip boundary condition in complex pore
geometries, are also implemented for the construction and the simulation of the
realistic shale pores from 3D nanometer-resolution stack images. Our code is
validated for accuracy and compared against the CPU counterpart for speedup. In
our benchmark tests, the code delivers nearly perfect strong scaling and weak
scaling (with up to 512 million particles) on up to 512 K20X GPUs on Oak Ridge
National Laboratory's (ORNL) Titan supercomputer. Moreover, a single-GPU
benchmark on ORNL's SummitDev and IBM's AC922 suggests that the host-to-device
NVLink can boost performance over PCIe by a remarkable 40\%. Lastly, we
demonstrate, through a flow simulation in realistic shale pores, that the CPU
counterpart requires 840 Power9 cores to rival the performance delivered by our
package with four V100 GPUs on ORNL's Summit architecture. This simulation
package enables quick-turnaround and high-throughput mesoscopic numerical
simulations for investigating complex flow phenomena in nano- to micro-porous
rocks with realistic pore geometries
Improvement of Fluid Simulation Runtime of Smoothed Particle Hydrodynamics by Using Graphics Processing Unit (GPU)
This study concerns an implementation of smoothed particle hydrodynamics (SPH) fluid simulation on a graphics processing unit (GPU) using the Compute Unified Device Architecture's (CUDA) parallel programming. A bookkeeping method for the neighbor search algorithm was incorporated to accelerate calculations. Based on sequence code profiling of the SPH method, particle interaction computation "“ which comprises the calculation of the continuity equation and the momentum conservation equation "“ consumes 95.2% of the calculation time. In this paper, an improvement of the calculation is proposed by calculating the particle interaction part on the GPU and by using a bookkeeping algorithm to restrict the calculation only to contributed particles. Three aspects are addressed in this paper: firstly, speed-up of the CUDA parallel programming computation as a function of the number of particles used in the simulation; secondly, the influence of double precision and single precision schemes on the computational acceleration; and thirdly, calculation accuracy with respect to the number of particles. Scott Russell's wave generator was implemented for a 2D case and a 3D dam-break. The results show that the proposed method was succesfull in accelerating the SPH simulation on the GPU
A fast framework construction and visualization method for particle-based fluid
© 2017, The Author(s). Fast and vivid fluid simulation and visualization is a challenge topic of study in recent years. Particle-based simulation method has been widely used in the art animation modeling and multimedia field. However, the requirements of huge numerical calculation and high quality of visualization usually result in a poor computing efficiency. In this work, in order to improve those issues, we present a fast framework for 3D fluid fast constructing and visualization which parallelizes the fluid algorithm based on the GPU computing framework and designs a direct surface visualization method for particle-based fluid data such as WCSPH, IISPH, and PCISPH. Considering on conventional polygonization or adaptive mesh methods may incur high computing costs and detail losses, an improved particle-based method is provided for real-time fluid surface rendering with the screen-space technology and the utilities of the modern graphics hardware to achieve the high performance rendering; meanwhile, it effectively protects fluid details. Furthermore, to realize the fast construction of scenes, an optimized design of parallel framework and interface is also discussed in our paper. Our method is convenient to enforce, and the results demonstrate a significant improvement in the performance and efficiency by being compared with several examples
GPU-accelerated simulation of colloidal suspensions with direct hydrodynamic interactions
Solvent-mediated hydrodynamic interactions between colloidal particles can
significantly alter their dynamics. We discuss the implementation of Stokesian
dynamics in leading approximation for streaming processors as provided by the
compute unified device architecture (CUDA) of recent graphics processors
(GPUs). Thereby, the simulation of explicit solvent particles is avoided and
hydrodynamic interactions can easily be accounted for in already available,
highly accelerated molecular dynamics simulations. Special emphasis is put on
efficient memory access and numerical stability. The algorithm is applied to
the periodic sedimentation of a cluster of four suspended particles. Finally,
we investigate the runtime performance of generic memory access patterns of
complexity for various GPU algorithms relying on either hardware cache
or shared memory.Comment: to appear in a special issue of Eur. Phys. J. Special Topics on
"Computer Simulations on GPUs
A Survey of Ocean Simulation and Rendering Techniques in Computer Graphics
This paper presents a survey of ocean simulation and rendering methods in
computer graphics. To model and animate the ocean's surface, these methods
mainly rely on two main approaches: on the one hand, those which approximate
ocean dynamics with parametric, spectral or hybrid models and use empirical
laws from oceanographic research. We will see that this type of methods
essentially allows the simulation of ocean scenes in the deep water domain,
without breaking waves. On the other hand, physically-based methods use
Navier-Stokes Equations (NSE) to represent breaking waves and more generally
ocean surface near the shore. We also describe ocean rendering methods in
computer graphics, with a special interest in the simulation of phenomena such
as foam and spray, and light's interaction with the ocean surface
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