high performance computing on graphics processing units: hgpu.org

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Fast Calculation of Electrostatic Potentials on the GPU or the ASIC MD-GRAPE-3

Tetsu Narumi, Kenji Yasuoka, Makoto Taiji, Francesco Zerbetto, Siegfried Hofinger

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Tags: Biomolecules, Biophysics, Chemistry, Molecular simulation, nVidia, nVidia GeForce GTX 280, Poisson Boltzmann

January 25, 2011 by hgpu

CUDASA: Compute Unified Device and Systems Architecture

M. Strengert, C. Muller, C. Dachsbacher, and T. Ertl

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Tags: Computer science, CUDA, GPU cluster, High-level Languages, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 8800 GTX, nVidia Quadro FX 5600

January 24, 2011 by hgpu

Sparse regularization in MRI iterative reconstruction using GPUs

Yue Zhuo, Bradley Sutton, Xiao-Long Wu, Justin Haldar, Wen-mei Hwu, Zhipei Liang

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Tags: CUDA, Image processing, Image reconstruction, MRI, nVidia, nVidia GeForce GTX 280, Sparse matrix

January 24, 2011 by hgpu

Exploiting More Parallelism from Applications Having Generalized Reductions on GPU Architectures

Xiao-Long Wu, Nady Obeid, Wen-Mei Hwu

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Tags: Algorithms, Computer science, CUDA, nVidia, Optimization

January 24, 2011 by hgpu

Multi-GPU Implementation for Iterative MR Image Reconstruction with Field Correction

Y. Zhuo, X-L. Wu, J. P. Haldar, W-M. W. Hwu, Z-P. Liang, and B. P. Sutton

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Tags: CUDA, Image processing, Image reconstruction, MRI, nVidia, Tesla S1070

January 24, 2011 by hgpu

Accelerating iterative field-compensated MR image reconstruction on GPUs

Yue Zhuo, Xiao-Long Wu, Justin P. Haldar, Wen-mei Hwu, Zhi-pei Liang, Bradley P. Sutton

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Tags: Conjugate gradient solver, CUDA, Image processing, Image reconstruction, Medicine, MRI, nVidia, nVidia GeForce GTX 280

January 24, 2011 by hgpu

Data Layout Transformation for Structured-Grid Codes on GPU

I-Jui Sung, Wen-Mei Hwu

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 280

January 24, 2011 by hgpu

Program Optimization Strategies for Data-Parallel Many-Core Processors

Shane Ryoo

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Optimization, Thesis

January 24, 2011 by hgpu

Efficient Parallel Scan Algorithms for GPUs

Shubhabrata Sengupta, Mark Harris, Michael Garland

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Package

January 24, 2011 by hgpu

Efficient Sparse Matrix-Vector Multiplication on CUDA

Nathan Bell and Michael Garland

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 280, Sparse matrix

January 24, 2011 by hgpu

Parallel Genetic Algorithms on Programmable Graphics Hardware

Qizhi Yu, Chongcheng Chen and Zhigeng Pan

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Tags: Algorithms, Cg, Computer science, Genetic programming, nVidia, nVidia GeForce 6800 GT

January 23, 2011 by hgpu

Evolutionary Computing on Consumer-Level Graphics Hardware

Ka-Ling Fok, Tien-TsinWong, Man-Leung Wong

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Tags: Algorithms, Computer science, Genetic programming, nVidia, nVidia GeForce 6800 Ultra, Shaders

January 23, 2011 by hgpu

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

See all packages

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high performance computing on graphics processing units: hgpu.org

Fast Calculation of Electrostatic Potentials on the GPU or the ASIC MD-GRAPE-3

CUDASA: Compute Unified Device and Systems Architecture

Sparse regularization in MRI iterative reconstruction using GPUs

Exploiting More Parallelism from Applications Having Generalized Reductions on GPU Architectures

Multi-GPU Implementation for Iterative MR Image Reconstruction with Field Correction

Accelerating iterative field-compensated MR image reconstruction on GPUs

Data Layout Transformation for Structured-Grid Codes on GPU

Program Optimization Strategies for Data-Parallel Many-Core Processors

Efficient Parallel Scan Algorithms for GPUs

Efficient Sparse Matrix-Vector Multiplication on CUDA

Parallel Genetic Algorithms on Programmable Graphics Hardware

Evolutionary Computing on Consumer-Level Graphics Hardware

Recent source codes

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

Most viewed papers (last 30 days)