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Sparse matrix computations on manycore GPU’s

Michael Garland

Tags: Algorithms, Computer science, CUDA, nVidia, Path problems, Programming techniques, Sparse matrix

June 2, 2011 by hgpu

Massively Parallel Finite Element Simulator for Full-Chip STI Stress Analysis

Jiying Xue, Xiaomeng Jiao, Yangdong Deng, Hao Qian, Dajie Zeng, Guoyu Li, Zhiping Yu

Tags: CUDA, Electronic design automation, FEM, Finite element method, nVidia

June 2, 2011 by hgpu

Accelerating All-Atom Normal Mode Analysis with Graphics Processing Unit

Li Liu, Xiaofeng Liu, Jiayu Gong, Hualiang Jiang, Honglin Li

Tags: Biology, Chemistry, CUDA, Macromolecule, Molecular dynamics, nVidia, Pharmaceuticals

June 2, 2011 by hgpu

MapCG: writing parallel program portable between CPU and GPU

Chuntao Hong, Dehao Chen, Wenguang Chen, Weimin Zheng, Haibo Lin

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Tags: Computer science, CUDA, High-level Languages, MapReduce, nVidia, nVidia GeForce GTX 280, Programming techniques

June 2, 2011 by hgpu

Swarm’s flight: Accelerating the particles using C-CUDA

Lucas de P. Veronese, Renato A. Krohling

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

June 2, 2011 by hgpu

Spherical harmonic transform on heterogeneous architectures using hybrid programming

Mikolaj Szydlarski, Pierre Esterie, Joel Falcou, Laura Grigori, Radek Stompor

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Tags: Computer science, CUDA, GPU cluster, Hybrid computing, MPI, nVidia, OpenMP, Tesla S1070

June 2, 2011 by hgpu

GPS forward model computing study on CPU/GPU co-processing parallel system using CUDA

Fukang Yin, Fengshun Lu, Xiaoqun Cao, Junqiang Song

Tags: Computational modelling, Computer science, CUDA, Earth and Space Sciences, GPU cluster, nVidia, nVidia GeForce GTX 480, Weather prediction

June 1, 2011 by hgpu

GPUMLib: A new Library to combine Machine Learning algorithms with Graphics Processing Units

N. Lopes, B. Ribeiro, R. Quintas

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Source codes

Tags: Computer science, CUDA, Machine learning, nVidia, Package

June 1, 2011 by hgpu

A GPU/CUDA implementation of the collection-diffusion model to compute SER of large area and complex circuits

J.L. Autran, S. Uznanski, S. Martinie, P. Roche, G. Gasiot, D. Munteanu

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Tags: Computer science, CUDA, Fault simulation, Hardware Architecture, Memory, nVidia, Physics, Tesla C1060

June 1, 2011 by hgpu

CUDA Accelerated LTL Model Checking

Jiri Barnat, Lubos Brim, Milan Ceska, Tomas Lamr

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 280

June 1, 2011 by hgpu

The Parallel Processing Based on CUDA for Convolution Filter FDK Reconstruction of CT

Benyi Shi, Sihai Chen, Feifei Huang, Cheng Wang, Kun Bi

Tags: Computed tomography, CT, CUDA, Image reconstruction, Medicine, nVidia, Tomography

June 1, 2011 by hgpu

Robust Low Complexity Feature Tracking using CUDA

R. Phull, P. Mainali, Qiong Yang, H. Sips, G. Lafruit

Tags: Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 280

June 1, 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

Programming

Sparse matrix computations on manycore GPU’s

Massively Parallel Finite Element Simulator for Full-Chip STI Stress Analysis

Accelerating All-Atom Normal Mode Analysis with Graphics Processing Unit

MapCG: writing parallel program portable between CPU and GPU

Swarm’s flight: Accelerating the particles using C-CUDA

Spherical harmonic transform on heterogeneous architectures using hybrid programming

GPS forward model computing study on CPU/GPU co-processing parallel system using CUDA

GPUMLib: A new Library to combine Machine Learning algorithms with Graphics Processing Units

A GPU/CUDA implementation of the collection-diffusion model to compute SER of large area and complex circuits

CUDA Accelerated LTL Model Checking

The Parallel Processing Based on CUDA for Convolution Filter FDK Reconstruction of CT

Robust Low Complexity Feature Tracking using CUDA

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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