high performance computing on graphics processing units: hgpu.org

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Molecular dynamics simulations with many-body potentials on multiple GPUs – the implementation, package and performance

Qing Hou, Min Li, Yulu Zhou, Jiechao Cui, Zhenguo Cui, Jun Wang

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Tags: Computational Physics, CUDA, GPU cluster, Materials Science, Molecular dynamics, nVidia, Physics, Tesla C2050

January 2, 2013 by hgpu

Toward GPU-accelerated Traffic Simulation and Its Real-Time Challenge

Manato Hirabayashi, Shinpei Kato, Masato Edahiro, Yuki Sugiyama

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Tags: Computational Physics, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti

December 23, 2012 by hgpu

IceCubes GPGPU’s cluster for extensive MC production

Martin Merck, Dmitry Chirkin, Juan Carlos Diaz Velez, Heath Skarlupka

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Tags: Computational Physics, CUDA, GPU cluster, Monte Carlo simulation, Nuclear physics, nVidia, Particle physics and field theory, Physics, Raytracing, Tesla M2070

December 20, 2012 by hgpu

Ferrofluid Simulations with the Barnes-Hut Algorithm on Graphics Processing Units

A. Yu. Polyakov, T. V. Lyutyy, S. Denisov, V. V. Reva, P. Hanggi

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Tags: Computational Physics, CUDA, Fluid dynamics, Fluid simulation, Numerical simulation, nVidia, Tesla M2050

December 14, 2012 by hgpu

Gauge Field Generation on Large-Scale GPU-Enabled Systems

Frank Winter

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Tags: Computational Physics, CUDA, High Energy Physics - Lattice, nVidia, Physics, QCD, Tesla M2090

December 5, 2012 by hgpu

Molecular dynamics for long-range interacting systems on Graphic Processing Units

Tarcisio M. Rocha Filho

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Tags: Algorithms, Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 690, Physics, Statistical Mechanics

December 4, 2012 by hgpu

A Customized 3D GPU Poisson Solver for Free BCs

Nazim Dugan, Luigi Genovese, Stefan Goedecker

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Tags: Computational Physics, CUDA, nVidia, Physics, Poisson equation, Tesla M2090

November 26, 2012 by hgpu

Accelerated molecular dynamics force evaluation on graphics processing units for thermal conductivity calculations

Zheyong Fan, Topi Siro, Ari Harju

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Tags: Computational Physics, Condensed matter, CUDA, Materials Science, Molecular dynamics, nVidia, Physics, Tesla M2070

November 19, 2012 by hgpu

Massively parallel Monte Carlo for many-particle simulations on GPUs

Joshua A. Anderson, Eric Jankowski, Thomas L. Grubb, Michael Engel, Sharon C. Glotzer

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Tags: Algorithms, Computational Physics, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 680, Particle simulation, Physics

November 8, 2012 by hgpu

Computational Physics on Graphics Processing Units

Ari Harju, Topi Siro, Filippo Federici-Canova, Samuli Hakala, Teemu Rantalaiho

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Tags: Computational Physics, High Energy Physics - Lattice, Molecular dynamics, Physics, Review

October 31, 2012 by hgpu

GPU-Based Asynchronous Global Optimization with Particle Swarm

M. P. Wachowiak, A. E. Lambe Foster

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Tags: Biological Physics, Computational Physics, CUDA, nVidia, Particle swarm optimization, Physics, Tesla S1070

October 25, 2012 by hgpu

A short guide to CUDA C: For physicists with multi-core graphics cards

David Plotzki

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Source codes

Tags: Computational Physics, Computer science, CUDA, nVidia, nVidia Quadro NVS 3100 M, Package, Physics, Tesla C1060, Tutorial

October 19, 2012 by hgpu

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

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high performance computing on graphics processing units: hgpu.org

Molecular dynamics simulations with many-body potentials on multiple GPUs – the implementation, package and performance

Toward GPU-accelerated Traffic Simulation and Its Real-Time Challenge

IceCubes GPGPU’s cluster for extensive MC production

Ferrofluid Simulations with the Barnes-Hut Algorithm on Graphics Processing Units

Gauge Field Generation on Large-Scale GPU-Enabled Systems

Molecular dynamics for long-range interacting systems on Graphic Processing Units

A Customized 3D GPU Poisson Solver for Free BCs

Accelerated molecular dynamics force evaluation on graphics processing units for thermal conductivity calculations

Massively parallel Monte Carlo for many-particle simulations on GPUs

Computational Physics on Graphics Processing Units

GPU-Based Asynchronous Global Optimization with Particle Swarm

A short guide to CUDA C: For physicists with multi-core graphics cards

Recent source codes

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

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