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On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs

Fang Xu, Wei Xu, Mel Jones, Bettina Keszthelyi, John Sedat, David Agard, Klaus Mueller

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Tags: Cg, Computed tomography, CT, CUDA, Image reconstruction, Medicine, nVidia, nVidia GeForce 8800 GTX

November 28, 2010 by hgpu

Complexity effective memory access scheduling for many-core accelerator architectures

George L. Yuan, Ali Bakhoda, Tor M. Aamodt

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Tags: Architecture, Computer science, CUDA, Hardware, Memory, nVidia

November 28, 2010 by hgpu

Accelerating error correction in high-throughput short-read DNA sequencing data with CUDA

Haixiang Shi, B. Schmidt, Weiguo Liu, W. Muller-Wittig

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Tags: Algorithms, Computer science, CUDA, Error recovery, nVidia, nVidia GeForce GTX 280

November 27, 2010 by hgpu

Parallel reconstruction of neighbor-joining trees for large multiple sequence alignments using CUDA

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 280, Sequence alignment, Smith-Waterman algorithm

November 27, 2010 by hgpu

Towards Accelerated Computation of Atmospheric Equations Using CUDA

Vaclav Simek, Radim Dvorak, Frantisek Zboril, Jiri Kunovsky

Tags: CUDA, Earth and Space Sciences, nVidia, Partial differential equations, PDEs

November 27, 2010 by hgpu

Boids that see: Using self-occlusion for simulating large groups on GPUs

Alessandro R. Da Silva, Wallace S. Lages, Luiz Chaimowicz

Tags: Artificial intelligence, Computer science, CUDA, Games, nVidia

November 27, 2010 by hgpu

Particle-Based Multiple Irregular Volume Rendering on CUDA

Ding Zhongming, Takuma Kawamura, Naohisa Sakamoto, Koji Koyamada

Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, Rendering

November 27, 2010 by hgpu

Fast Conjugate Gradients with Multiple GPUs

Ali Cevahir, Akira Nukada, Satoshi Matsuoka

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Tags: Computer science, Conjugate gradient solver, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 8800 GTS

November 27, 2010 by hgpu

A Note on Auto-tuning GEMM for GPUs

Yinan Li, Jack Dongarra, Stanimire Tomov

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

November 27, 2010 by hgpu

Modeling of tsunami waves and atmospheric swirling flows with graphics processing unit

Jessica Schmidt, Cecile Piret, Nan Zhang, Benjamin J. Kadlec, David A. Yuen, Yingchun Liu, Grady Barrett Wright, Erik O. D. Sevre

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Tags: CUDA, Earth and Space Sciences, Geoscience, nVidia, nVidia GeForce 8600 M GT, nVidia Quadro FX 5600

November 27, 2010 by hgpu

Accelerating Lattice Boltzmann Fluid Flow Simulations Using Graphics Processors

Peter Bailey, Joe Myre, Stuart D.C. Walsh, David J. Lilja, Martin O. Saar

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia GeForce 8800 GTX, nVidia GeForce 8800 Ultra, nVidia GeForce 9800 GX2

November 27, 2010 by hgpu

Accelerating geoscience and engineering system simulations on graphics hardware

Stuart D. C. Walsh, Martin O. Saar, Peter Bailey, David J. Lilja

Tags: CUDA, Earth and Space Sciences, Geoscience, Lattice Boltzmann model, nVidia, Seismology

November 27, 2010 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

Programming

On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs

Complexity effective memory access scheduling for many-core accelerator architectures

Accelerating error correction in high-throughput short-read DNA sequencing data with CUDA

Parallel reconstruction of neighbor-joining trees for large multiple sequence alignments using CUDA

Towards Accelerated Computation of Atmospheric Equations Using CUDA

Boids that see: Using self-occlusion for simulating large groups on GPUs

Particle-Based Multiple Irregular Volume Rendering on CUDA

Fast Conjugate Gradients with Multiple GPUs

A Note on Auto-tuning GEMM for GPUs

Modeling of tsunami waves and atmospheric swirling flows with graphics processing unit

Accelerating Lattice Boltzmann Fluid Flow Simulations Using Graphics Processors

Accelerating geoscience and engineering system simulations on 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

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