high performance computing on graphics processing units: hgpu.org

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Computitional intensive Tasks in Multimedia Signal Processing

Yan Liu

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Tags: Algorithms, Compression, CUDA, FFT, nVidia, Overview, Signal processing

October 10, 2011 by hgpu

A GPU-Accelerated Parallel Preconditioner for the Solution of the Boltzmann Transport Equation for Semiconductors

Karl Rupp, Ansgar Jungel, Tibor Grasser

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Tags: Boltzmann equation, Computer science, Differential equations, Factorization, nVidia, nVidia GeForce GTX 580, OpenCL, Partial differential equations, PDEs

October 10, 2011 by hgpu

Anti-parallel Patterns in Fine-grain Data-parallel Programs

Jan Cornelis

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Tags: Benchmarking, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce 8500 GT, nVidia GeForce GTX 280, Performance, Thesis

October 10, 2011 by hgpu

Benchmarks Based on Anti-Parallel Patterns for the Evaluation of GPUs

Jan G. Cornelis, Jan Lemeire

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Tags: ATI, ATI Radeon HD 5850, Benchmarking, Computer science, nVidia, nVidia GeForce GTX 280, OpenCL

October 10, 2011 by hgpu

Evaluation of GPU Architectures Using Spiking Neural Networks

Vivek K. Pallipuram, Mohammad A. Bhuiyan, Melissa C. Smith

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Tags: ATI, ATI Radeon HD 5870, Computer science, Neural networks, nVidia, OpenCL, Optimization, Performance, Presentation, Tesla C2050

October 10, 2011 by hgpu

Towards an Effective Unified Programming Model for Many-Cores

Ana Lucia Varbanescu, Pieter Hijma, Rob V. van Nieuwpoort, Henri E. Bal

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Tags: ATI, Cell processor, Computer science, nVidia, OpenCL, Optimization, Programming techniques

October 10, 2011 by hgpu

Denoising Volumetric Data on GPU

Jan Horacek, Jan Kolomaznik, Josef Pelikan, Martin Horak

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Tags: Algorithms, Image processing, Medicine, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 275, nVidia GeForce GTX 460, OpenCL, Signal denoising, Tomography

October 10, 2011 by hgpu

Data-Parallel Construction of delta_N-Nets with Maximum Dispersion

Peter Zinterhof

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Tags: Algorithms, Computational Complexity, Computer science, Nearest neighbour, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480, OpenCL, OpenMPI, Search, Tesla C2050

October 10, 2011 by hgpu

GPUs, a New Tool of Acceleration in CFD: Efficiency and Reliability on Smoothed Particle Hydrodynamics Methods

Alejandro C. Crespo, Jose M. Dominguez, Anxo Barreiro, Moncho Gomez-Gesteira, Benedict D. Rogers

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Tags: CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Performance, Tesla M1060, Visualization

October 10, 2011 by hgpu

Multifrontal computations on GPUs and their multi-core hosts

Robert F. Lucas, Gene Wagenbreth, Dan M. Davis, Roger Grimes

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Tags: Computer science, CUDA, Factorization, nVidia, Performance, Sparse matrix, Tesla C1060

October 7, 2011 by hgpu

Non-recursive beam search on GPU for formal concept analysis

W. B. Langdon, Shin Yoo, Mark Harman

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Tesla C2050

October 7, 2011 by hgpu

Investigation on the Use of GPGPU for Fast Sparse Matrix Factorization

Ye Tian, Bin Zhou, Yutong Zhang, Ka Wing Chan

Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, Sparse matrix

October 7, 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

Computitional intensive Tasks in Multimedia Signal Processing

A GPU-Accelerated Parallel Preconditioner for the Solution of the Boltzmann Transport Equation for Semiconductors

Anti-parallel Patterns in Fine-grain Data-parallel Programs

Benchmarks Based on Anti-Parallel Patterns for the Evaluation of GPUs

Evaluation of GPU Architectures Using Spiking Neural Networks

Towards an Effective Unified Programming Model for Many-Cores

Denoising Volumetric Data on GPU

Data-Parallel Construction of delta_N-Nets with Maximum Dispersion

GPUs, a New Tool of Acceleration in CFD: Efficiency and Reliability on Smoothed Particle Hydrodynamics Methods

Multifrontal computations on GPUs and their multi-core hosts

Non-recursive beam search on GPU for formal concept analysis

Investigation on the Use of GPGPU for Fast Sparse Matrix Factorization

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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