high performance computing on graphics processing units: hgpu.org

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Optimization strategies for parallel CPU and GPU implementations of a meshfree particle method

Jose M. Dominguez, Alejandro J.C. Crespo, Moncho Gomez-Gesteira

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Tags: Computational Engineering, Computer science, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 480, OpenMP, Optimization, Performance, Tesla C1060

October 18, 2011 by hgpu

The Lattice Boltzmann Simulation on Multi-GPU Systems

Thor Kristian Valderhaug

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Tags: ATI, ATI Radeon HD 5870, Fluid dynamics, Lattice Boltzmann model, MPI, nVidia, OpenCL, Tesla C1060, Tesla C2070, Tesla S2070, Tesla T10, Thesis

October 17, 2011 by hgpu

GPU Computing Gems: Jade Edition

Wen-mei W. Hwu

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Tags: Algorithms, Book, Cellular automata, Computational finance, Computer science, Computer vision, CUDA, Finance, Fluid dynamics, Games, GPU cluster, nVidia

October 14, 2011 by hgpu

Fast Multipole Method vs. Spectral Method for the Simulation of Isotropic Turbulence on GPUs

Rio Yokota, L. A. Barba

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Tags: Algorithms, Computational Physics, CUDA, Fast multipole method, FFT, Fluid dynamics, Numerical Analysis, nVidia, Spectral methods, Tesla C2070

October 14, 2011 by hgpu

GPUs, a New Tool of Acceleration in CFD: Efficiency and Reliability on Smoothed Particle Hydrodynamics Methods

Alejandro C. Crespo, Jose M. Dominguez, Anxo Barreiro, Moncho Gomez-Gesteira, Benedict D. Rogers

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Source codes

Tags: CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Performance, Tesla M1060, Visualization

October 10, 2011 by hgpu

Performance Analysis and Optimisation 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, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 260, OpenMP, Partial differential equations, PDEs, Tesla C2050

October 5, 2011 by hgpu

A Massive Data Parallel Computational Framework on Petascale/Exascale Hybrid Computer Systems

Marek Blazewicz, Steven R. Brandt, Peter Diener, David M. Koppelman, Krzysztof Kurowski, Frank Loffler, Erik Schnetter, Jian Tao

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, nVidia, OpenCL, Optimization, Package, Programming techniques, Tesla S1070

October 4, 2011 by hgpu

Finite element assembly strategies on multi-and many-core architectures

G. R. Markall, A. Slemmer, D. A .Ham, P. H. J. Kelly, C. D. Cantwell, S. J. Sherwin

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Tags: Algorithms, ATI, ATI Radeon HD 5870, CUDA, FEM, Finite element method, Fluid dynamics, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Spectral elements

October 4, 2011 by hgpu

Development of a Chemically Reacting Flow Solver on the Graphic Processing Units

Hai Le

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Tags: Algorithms, CUDA, Finite volume method, Fluid dynamics, nVidia, Optimization, Tesla C2050

October 2, 2011 by hgpu

Running unstructured grid-based CFD solvers on modern graphics hardware

Andrew Corrigan, Fernando F. Camelli, Rainald Lohner, John Wallin

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Tags: Algorithms, CUDA, Fluid dynamics, nVidia, Tesla

September 26, 2011 by hgpu

The TheLMA project: Multi-GPU implementation of the lattice Boltzmann method

Christian Obrecht, Frederic Kuznik, Bernard Tourancheau, Jean-Jacques Roux

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

September 19, 2011 by hgpu

cuIBM — A GPU-accelerated Immersed Boundary Method

Simon K Layton, Anush Krishnan, Lorena A. Barba

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Tags: CUDA, Fluid dynamics, Linear Algebra, nVidia, Optimization, Tesla C2050

September 19, 2011 by hgpu

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Optimization strategies for parallel CPU and GPU implementations of a meshfree particle method

The Lattice Boltzmann Simulation on Multi-GPU Systems

GPU Computing Gems: Jade Edition

Fast Multipole Method vs. Spectral Method for the Simulation of Isotropic Turbulence on GPUs

GPUs, a New Tool of Acceleration in CFD: Efficiency and Reliability on Smoothed Particle Hydrodynamics Methods

Performance Analysis and Optimisation of the OP2 Framework on Many-core Architectures

A Massive Data Parallel Computational Framework on Petascale/Exascale Hybrid Computer Systems

Finite element assembly strategies on multi-and many-core architectures

Development of a Chemically Reacting Flow Solver on the Graphic Processing Units

Running unstructured grid-based CFD solvers on modern graphics hardware

The TheLMA project: Multi-GPU implementation of the lattice Boltzmann method

cuIBM — A GPU-accelerated Immersed Boundary Method

Recent source codes

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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