high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Solving $k$-Nearest Vector Problem on Multiple Graphics Processors

Kimikazu Kato, Tikara Hosino

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Tags: Computer science, CUDA, Data Structures and Algorithms, Information Retrieval, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 280

November 8, 2010 by hgpu

Analysing Astronomy Algorithms for GPUs and Beyond

Benjamin R. Barsdell, David G. Barnes, Christopher J. Fluke

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Tags: Algorithms, Astrophysics, Instrumentation and Methods for Astrophysics, Physics

November 8, 2010 by hgpu

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

Anthony Lee, Christopher Yau, Michael B. Giles, Arnaud Doucet, Christopher C. Holmes

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Source codes

Tags: CUDA, Mathematics, Monte Carlo simulation, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 280, Package, Statistics

November 8, 2010 by hgpu

N-Body Simulations on GPUs

Erich Elsen, V. Vishal, Mike Houston, Vijay Pande, Pat Hanrahan, Eric Darve

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Tags: ATI, ATI Radeon X1900, ATI Stream, Brook, Computational Engineering, Computer science, Molecular dynamics, N-body simulation, Stellar dynamics

November 8, 2010 by hgpu

Integrating Post-Newtonian Equations on Graphics Processing Units

Frank Herrmann, John Silberholz, Matias Bellone, Gustavo Guerberoff, Manuel Tiglio

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Tags: Astrophysics, Cosmology and Extragalactic Astrophysics, CUDA, Earth and Planetary Astrophysics, Galaxy Astrophysics, General Relativity and Quantum Cosmology, High Energy Astrophysical Phenomena, Instrumentation and Methods for Astrophysics, nVidia, Physics, Solar and Stellar Astrophysics, Tesla S1070

November 8, 2010 by hgpu

Graphic-Card Cluster for Astrophysics (GraCCA) – Performance Tests

Hsi-Yu Schive, Chia-Hung Chien, Shing-Kwong Wong, Yu-Chih Tsai, Tzihong Chiueh

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Tags: Astrophysics, CUDA, GPU cluster, Gravitation, MPI, N-body simulation, nVidia, nVidia GeForce 8800 GTX, Physics, Stellar dynamics

November 8, 2010 by hgpu

Quantile Mechanics II: Changes of Variables in Monte Carlo methods and a GPU-Optimized Normal Quantile

William T. Shaw, Nick Brickman

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Tags: Computational finance, CUDA, Finance, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia Quadro FX 4800, Risk Management, Statistical Finance

November 8, 2010 by hgpu

Calculation of HELAS amplitudes for QCD processes using graphics processing unit (GPU)

K. Hagiwara, J. Kanzaki, N. Okamura, D. Rainwater, T. Stelzer

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Tags: Computational Physics, CUDA, High Energy Physics - Phenomenology, nVidia, nVidia GeForce GTX 280, Physics

November 8, 2010 by hgpu

GPUs for data processing in the MWA

S. Ord, L. Greenhill, R. Wayth, D. Mitchell, K. Dale, H. Pfister, R. G. Edgar

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Physics, Tesla C1060

November 8, 2010 by hgpu

GPU accelerated Monte Carlo simulation of the 2D and 3D Ising model

Tobias Preis, Peter Virnau, Wolfgang Paul, Johannes J. Schneider

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Tags: CUDA, Finite size scaling, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, Package, Phase transition, Physics

November 8, 2010 by hgpu

Multifold Acceleration of Neural Network Computations Using GPU

Alexander Guzhva, Sergey Dolenko, Igor Persiantsev

Tags: Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 260

November 8, 2010 by hgpu

Hybrid CUDA, OpenMP, and MPI parallel programming on multicore GPU clusters

Chao-Tung Yang, Chih-Lin Huang, Cheng-Fang Lin

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Tags: Computer science, CUDA, GPU cluster, Hybrid computing, MPI, nVidia, OpenMP, Tesla C1060, Tesla S1070

November 8, 2010 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Solving $k$-Nearest Vector Problem on Multiple Graphics Processors

Analysing Astronomy Algorithms for GPUs and Beyond

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

N-Body Simulations on GPUs

Integrating Post-Newtonian Equations on Graphics Processing Units

Graphic-Card Cluster for Astrophysics (GraCCA) – Performance Tests

Quantile Mechanics II: Changes of Variables in Monte Carlo methods and a GPU-Optimized Normal Quantile

Calculation of HELAS amplitudes for QCD processes using graphics processing unit (GPU)

GPUs for data processing in the MWA

GPU accelerated Monte Carlo simulation of the 2D and 3D Ising model

Multifold Acceleration of Neural Network Computations Using GPU

Hybrid CUDA, OpenMP, and MPI parallel programming on multicore GPU clusters

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

Most viewed papers (last 30 days)