high performance computing on graphics processing units: hgpu.org

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A Massive Data Parallel Computational Framework on Petascale/Exascale Hybrid Computer Systems

Marek Blazewicz, Steven R. Brandt, Peter Diener, David M. Koppelman, Krzysztof Kurowski, Frank Loffler, Erik Schnetter, Jian Tao

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, nVidia, OpenCL, Optimization, Package, Programming techniques, Tesla S1070

October 4, 2011 by hgpu

Architecture-Aware Optimization on a 1600-core Graphics Processor

Mayank Daga, Thomas R.W. Scogland, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 5870, Cluster computing, Computer science, CUDA, Molecular modeling, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Tesla C2050

October 4, 2011 by hgpu

GPU Algorithms for Diamond-based Multiresolution Terrain Processing

M. Adil Yalcin, Kenneth Weiss, Leila De Floriani

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Tags: 3D Graphics and Realism, Algorithms, Computer science, nVidia, nVidia GeForce GTX 260, OpenCL, OpenGL, Rendering, Tessellation, Visualization

October 4, 2011 by hgpu

Finite element assembly strategies on multi-and many-core architectures

G. R. Markall, A. Slemmer, D. A .Ham, P. H. J. Kelly, C. D. Cantwell, S. J. Sherwin

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Tags: Algorithms, ATI, ATI Radeon HD 5870, CUDA, FEM, Finite element method, Fluid dynamics, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Spectral elements

October 4, 2011 by hgpu

Berkeley Dwarfs on CUDA

Paul Springer

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Tesla C2050, Thesis

October 4, 2011 by hgpu

Optimization of the Gaussian Mixture Model Evaluation on GPU

Jan Vanek, Jan Trmal, Josef V. Psutka, Josef Psutka

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 240, nVidia GeForce GTX 260, OpenCL, Optimization, Speech recognition

October 4, 2011 by hgpu

Acceleration of Radiance for Lighting Simulation by Using Parallel Computing with OpenCL

W. Zuo, A. McNeil, M. Wetter, E.S. Lee

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Tags: Algorithms, Computer science, Matrix multiplication, nVidia, nVidia GeForce GTX 460, OpenCL, Raytracing

October 4, 2011 by hgpu

Tranformation of CPU-based Applications To Leverage on Graphics Processors using CUDA

Fawnizu Azmadi Hussin, Anas Mohd Nazlee, Noohul Basheer Zain Ali

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Tags: Algorithms, Computer science, CUDA, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 260, Performance, Programming techniques, Security

October 3, 2011 by hgpu

Parallel Game Tree Search Using GPU

L'ubomir Lackovic

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Games, Graph theory, nVidia, nVidia GeForce GTX 460

October 3, 2011 by hgpu

Implementation of the optimization algorithms on GPGPU architecture and multi-cores

Li Liang

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Tags: Algorithms, Computer science, CUDA, Neural networks, nVidia, OpenCL, Optimization

October 3, 2011 by hgpu

GPU-Accelerated DNA Distance Matrix Computation

Zhi Ying, Xinhua Lin, Simon Chong-Wee See, Minglu Li

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Tags: ATI, ATI Radeon HD 5850, Bioinformatics, Biology, Genetics, nVidia, OpenCL, Performance, Tesla C2050

October 3, 2011 by hgpu

Parallel SAT-Solving with OpenCL

Sander Beckers, Gorik De Samblanx, Floris De Smedt, Toon Goedeme, Lars Struyf, Joost Vennekens

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Tags: Algorithms, Computer science, nVidia, OpenCL, SAT

October 3, 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

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high performance computing on graphics processing units: hgpu.org

A Massive Data Parallel Computational Framework on Petascale/Exascale Hybrid Computer Systems

Architecture-Aware Optimization on a 1600-core Graphics Processor

GPU Algorithms for Diamond-based Multiresolution Terrain Processing

Finite element assembly strategies on multi-and many-core architectures

Berkeley Dwarfs on CUDA

Optimization of the Gaussian Mixture Model Evaluation on GPU

Acceleration of Radiance for Lighting Simulation by Using Parallel Computing with OpenCL

Tranformation of CPU-based Applications To Leverage on Graphics Processors using CUDA

Parallel Game Tree Search Using GPU

Implementation of the optimization algorithms on GPGPU architecture and multi-cores

GPU-Accelerated DNA Distance Matrix Computation

Parallel SAT-Solving with OpenCL

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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