high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming » CUDA

Running the NIM Next-Generation Weather Model on GPUs

Mark W. Govett, Jacques Middlecoff, Tom Henderson

Tags: CUDA, Earth and Space Sciences, nVidia, Weather Prediction Model

November 9, 2010 by hgpu

Fast and informative flow simulations in a building by using fast fluid dynamics model on graphics processing unit

Wangda Zuo, Qingyan Chen

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Tags: CUDA, Fluid dynamics, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce 8800 GTX

November 9, 2010 by hgpu

Gravitational tree-code on graphics processing units: implementation in CUDA

Evghenii Gaburov, Jeroen Bedorf, Simon P. Zwart

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce 8800 Ultra, Package, Physics

November 9, 2010 by hgpu

Efficient pseudo-random number generators for biomolecular simulations on graphics processors

A. Zhmurov, K. Rybnikov, Y. Kholodov, V. Barsegov

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Tags: Biological Physics, Chemical Physics, CUDA, nVidia, nVidia GeForce GTX 295, Physics, Pseudo-random number generators

November 9, 2010 by hgpu

Massively parallel differential evolution-pattern search optimization with graphics hardware acceleration: an investigation on bound constrained optimization problems

Weihang Zhu

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Tags: Computer science, CUDA, Differential evolution, Finance, nVidia, nVidia GeForce GTX 280, Pattern Search

November 9, 2010 by hgpu

ABC-SysBio–approximate Bayesian computation in Python with GPU support

Juliane Liepe, Chris Barnes, Erika Cule, Kamil Erguler, Paul Kirk, Tina Toni, Michael P. H. Stumpf

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Tags: Bioinformatics, Biology, CUDA, nVidia, Package, Python

November 9, 2010 by hgpu

DiVinE-CUDA – A Tool for GPU Accelerated LTL Model Checking

Jiri Barnat, Lubos Brim, Milan Ceska

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Tags: Computer science, CUDA, Distributed computing, nVidia, nVidia GeForce GTX 280, Software Engineering

November 9, 2010 by hgpu

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

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

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

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

Programming

Running the NIM Next-Generation Weather Model on GPUs

Fast and informative flow simulations in a building by using fast fluid dynamics model on graphics processing unit

Gravitational tree-code on graphics processing units: implementation in CUDA

Efficient pseudo-random number generators for biomolecular simulations on graphics processors

Massively parallel differential evolution-pattern search optimization with graphics hardware acceleration: an investigation on bound constrained optimization problems

ABC-SysBio–approximate Bayesian computation in Python with GPU support

DiVinE-CUDA – A Tool for GPU Accelerated LTL Model Checking

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

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

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

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)