high performance computing on graphics processing units: hgpu.org

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Development of a GPU-based Monte Carlo dose calculation code for coupled electron-photon transport

Xun Jia, Xuejun Gu, Josep Sempau, Dongju Choi, Amitava Majumdar, Steve B. Jiang

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Tags: CUDA, Medical Physics, Medicine, Monte Carlo simulation, nVidia, Physics, Radiotherapy, Tesla C1060

November 13, 2010 by hgpu

TWQCD’s dynamical DWF project

Ting-Wai Chiu, Tian-Shin Guu, Tung-Han Hsieh, Chao-Hsi Huang, Yu-Ying Lee, Yao-Yuan Mao, Kenji Ogawa, Po-Kai Tseng

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Tags: CUDA, High Energy Physics - Lattice, Monte Carlo simulation, MPI, nVidia, OpenMP, Physics, QCD, Tesla S1070

November 13, 2010 by hgpu

Enhanced molecular dynamics performance with a programmable graphics processor

D. C. Rapaport

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Tags: Chemistry, Computational chemistry, Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia Quadro FX 770 M, Physics

November 13, 2010 by hgpu

CUDAEASY – a GPU Accelerated Cosmological Lattice Program

Jani Sainio

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Tags: Astrophysics, Computational Physics, Cosmology and Extragalactic Astrophysics, CUDA, High Energy Physics - Phenomenology, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 260, Package

November 13, 2010 by hgpu

The role of multigrid algorithms for LQCD

Ronald Babich, James Brannick, Richard C. Brower, Michael A. Clark, Saul D. Cohen, James C. Osborn, Claudio Rebbi

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Tags: CUDA, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, Physics, QCD

November 13, 2010 by hgpu

Air pollution modelling using a graphics processing unit with CUDA

Ferenc Molnar Jr., Tamas Szakaly, Robert Meszaros, Istvan Lagzi

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Tags: Computational Physics, CUDA, Earth and Space Sciences, Medical Physics, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, Package, Physics

November 13, 2010 by hgpu

GPU-based Fast Low-dose Cone Beam CT Reconstruction via Total Variation

Xun Jia, Yifei Lou, John Lewis, Ruijiang Li, Xuejun Gu, Chunhua Men, William Y. Song, Steve B. Jiang

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Tags: Computed tomography, CT, CUDA, Image reconstruction, Medical Physics, nVidia, Physics, Tesla C1060

November 13, 2010 by hgpu

Tiling for Performance Tuning on Different Models of GPUs

Chang Xu, Steven R. Kirk, Samantha Jenkins

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 260, Performance

November 13, 2010 by hgpu

Advanced Architectures for Astrophysical Supercomputing

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

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia

November 12, 2010 by hgpu

RapidMind: Portability across Architectures and its Limitations

Iris Christadler, Volker Weinberg

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Tags: Cell processor, Computer science, CUDA, nVidia, Performance, Programming Languages, Tesla C1060, Tesla S1070

November 12, 2010 by hgpu

GPU-Based Volume Rendering of Noisy Multi-Spectral Astronomical Data

Amr H. Hassan, Christopher J. Fluke, David G. Barnes

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, MPI, nVidia

November 12, 2010 by hgpu

Real-time digital holographic microscopy observable in multi-view and multi-resolution

Tomoyoshi Shimobaba, Nobuyuki Masuda, Yasuyuki Ichihashi, Tomoyoshi Ito

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Tags: Biological Physics, Computational Physics, Computer holography, CUDA, nVidia, nVidia GeForce GTX 295, Optics, Package, Physics

November 12, 2010 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Development of a GPU-based Monte Carlo dose calculation code for coupled electron-photon transport

TWQCD’s dynamical DWF project

Enhanced molecular dynamics performance with a programmable graphics processor

CUDAEASY – a GPU Accelerated Cosmological Lattice Program

The role of multigrid algorithms for LQCD

Air pollution modelling using a graphics processing unit with CUDA

GPU-based Fast Low-dose Cone Beam CT Reconstruction via Total Variation

Tiling for Performance Tuning on Different Models of GPUs

Advanced Architectures for Astrophysical Supercomputing

RapidMind: Portability across Architectures and its Limitations

GPU-Based Volume Rendering of Noisy Multi-Spectral Astronomical Data

Real-time digital holographic microscopy observable in multi-view and multi-resolution

Recent source codes

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

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

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