high performance computing on graphics processing units: hgpu.org

hgpu.org » Fluid dynamics

Radiation Modeling Using the Uintah Heterogeneous CPU/GPU Runtime System

Alan Humphrey, Qingyu Meng, Martin Berzins, Todd Harman

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Tags: CUDA, Fluid dynamics, GPU cluster, Heterogeneous systems, MPI, nVidia, Partial differential equations, Pthreads, Task scheduling, Tesla M2090

May 11, 2012 by hgpu

Real-time particle simulation of fluids

Zsolt Horvath

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Tags: CUDA, Fluid dynamics, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce GT 540 M, Particle simulation

April 27, 2012 by hgpu

Solving incompressible two-phase flows on multi-GPU clusters

Peter Zaspel, Michael Griebel

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Tags: CUDA, Finite difference, Fluid dynamics, GPU cluster, Navier-Stokes equations, nVidia, Tesla C2050, Tesla S1070

April 16, 2012 by hgpu

Acceleration of CFD and data analysis using graphics processors

Ali Khajeh Saeed

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Tags: ATI, ATI FirePro V7800, ATI Stream, CUDA, Fluid dynamics, nVidia, Tesla C2070, Thesis

April 16, 2012 by hgpu

Fast GPU-based fluid simulations using SPH

Oystein E. Krog, Anne C. Elster

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Tags: CUDA, Fluid dynamics, Fluid simulation, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 470, Package, Tesla C2050

April 16, 2012 by hgpu

Shallow water simulations on multiple GPUs

Martin Lilleeng Saetra, Andre Rigland Brodtkorb

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Tags: CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 480, Tesla C2050, Tesla S1070

March 21, 2012 by hgpu

Performance analysis and optimization of the OP2 framework on many-core architectures

M.B. Giles, G.R. Mudalige, Z. Sharif, G. Markall, P.H.J. Kelly

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Tags: Benchmarking, Computer science, CUDA, Fluid dynamics, nVidia, OpenMP, Optimization, Package, Performance, Tesla C2050

March 15, 2012 by hgpu

GPU-Accelerated Large-Eddy Simulation of Turbulent Channel Flows

Rey DeLeon, Inanc Senocak

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Tags: CUDA, Fluid dynamics, GPU cluster, Numerical simulation, nVidia

March 10, 2012 by hgpu

CUDA-enabled LBM Flow Simulation around Three Equilateral Cylinders using GPU Computing Processor

Muhammad Shafiqul Alam, Liang Cheng

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia

February 27, 2012 by hgpu

Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units

Xiong QinGang, Li Bo, Xu Ji, Fang XiaoJian, Wang XiaoWei, Wang LiMin, He XianFeng, Ge Wei

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Tags: Algorithms, CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, MPI, Numerical simulation, nVidia, Tesla C2050

February 22, 2012 by hgpu

Multiscale Hemodynamics Using GPU Clusters

Mauro Bisson, Massimo Bernaschi, Simone Melchionna, Sauro Succi, Efthimios Kaxiras

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Tags: Biology, CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, Medicine, nVidia, Tesla C1060

February 17, 2012 by hgpu

Computational Fluid Dynamics using OpenCL – a Practical Introduction

T. Bednarz, Luke Domanski, J. A. Taylor

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Tags: Algorithms, Finite difference, Fluid dynamics, Navier-Stokes equations, nVidia, nVidia GeForce GT 330 M, OpenCL, Review

January 25, 2012 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

See all packages

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high performance computing on graphics processing units: hgpu.org

Radiation Modeling Using the Uintah Heterogeneous CPU/GPU Runtime System

Real-time particle simulation of fluids

Solving incompressible two-phase flows on multi-GPU clusters

Acceleration of CFD and data analysis using graphics processors

Fast GPU-based fluid simulations using SPH

Shallow water simulations on multiple GPUs

Performance analysis and optimization of the OP2 framework on many-core architectures

GPU-Accelerated Large-Eddy Simulation of Turbulent Channel Flows

CUDA-enabled LBM Flow Simulation around Three Equilateral Cylinders using GPU Computing Processor

Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units

Multiscale Hemodynamics Using GPU Clusters

Computational Fluid Dynamics using OpenCL – a Practical Introduction

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

Most viewed papers (last 30 days)