high performance computing on graphics processing units: hgpu.org

Programming

Implementing Domain-Specific Languages for Heterogeneous Parallel Computing

HyoukJoong Lee, Kevin J. Brown, Arvind K. Sujeeth, Hassan Chafi, Kunle Olukotun, Tiark Rompf, Martin Odersky

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, Optimization, Tesla C2050

October 28, 2011 by hgpu

Parallel Computing the Longest Common Subsequence (LCS) on GPUs: Efficiency and Language Suitability

Amine Dhraief, Raik Issaoui, Abdelfettah Belghith

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GT 430, OpenCL, Sequence alignment

October 28, 2011 by hgpu

The CUDA implementation of the method of lines for the curvature dependent flows

Tomas Oberhuber, Atsushi Suzuki, Vitezslav Zabka

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Tags: Algorithms, CUDA, Differential equations, Finite volume method, Image processing, Mathematics, nVidia, nVidia GeForce GTX 280, ODEs, Ordinary differential equations

October 27, 2011 by hgpu

Off-axis quantitative phase imaging processing using CUDA: toward real-time applications

Hoa Pham, Huafeng Ding, Nahil Sobh, Minh Do, Sanjay Patel, Gabriel Popescu

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 470 M, Real-time graphics, Visualization

October 27, 2011 by hgpu

Parallelization of Single Threaded Applications using OpenMP and CUDA/C

John Burns

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Tags: Computer science, CUDA, Databases, nVidia, OpenMP, Software Engineering

October 27, 2011 by hgpu

Efficient Implementation and Evaluation of Methods for the Estimation of Motion in Image Sequences

Robert Hegner

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 260, Optical flow, Package, Thesis

October 27, 2011 by hgpu

Efficient Implementation of Optical Flow Algorithm Based on Directional Filters on a GPU Using CUDA

Robert Hegner, Ivar Austvoll, Tom Ryen, Guido M. Schuster

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 260, Optical flow, Package

October 27, 2011 by hgpu

Dense Dynamic Programming on Multi GPU

Vincent Boyer, Didier El Baz, Moussa Elkihel

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

October 26, 2011 by hgpu

Precision and Performance: Floating Point and IEEE 754 Compliance for NVIDIA GPUs

Nathan Whitehead, Alex Fit-Florea

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Tags: Computer science, CUDA, nVidia, Precision

October 26, 2011 by hgpu

A case study on porting scientific applications to GPU/CUDA

Javier Delgado, Joao Gazolla, Esteban Clua, S. Masoud Sadjadi

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Tags: Computer science, CUDA, Earth and Space Sciences, Fortran, nVidia, nVidia GeForce 9300 M, nVidia GeForce 9400 M, Tesla S1070, Weather prediction

October 26, 2011 by hgpu

Quasars spectra classification with the help of GPU computing

P. Wasiewicz, K. Hryniewicz

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Tags: Astrophysics, CUDA, Databases, Numerical Analysis, nVidia, Package

October 26, 2011 by hgpu

Efficient Probabilistic Latent Semantic Indexing using Graphics Processing Unit

Eli Koffi Kouassi, Toshiyuki Amagasaa, Hiroyuki Kitagawa

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Tags: Algorithms, Computer science, CUDA, Data mining, nVidia, Semantic indexing, Tesla C2050

October 26, 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

Implementing Domain-Specific Languages for Heterogeneous Parallel Computing

Parallel Computing the Longest Common Subsequence (LCS) on GPUs: Efficiency and Language Suitability

The CUDA implementation of the method of lines for the curvature dependent flows

Off-axis quantitative phase imaging processing using CUDA: toward real-time applications

Parallelization of Single Threaded Applications using OpenMP and CUDA/C

Efficient Implementation and Evaluation of Methods for the Estimation of Motion in Image Sequences

Efficient Implementation of Optical Flow Algorithm Based on Directional Filters on a GPU Using CUDA

Dense Dynamic Programming on Multi GPU

Precision and Performance: Floating Point and IEEE 754 Compliance for NVIDIA GPUs

A case study on porting scientific applications to GPU/CUDA

Quasars spectra classification with the help of GPU computing

Efficient Probabilistic Latent Semantic Indexing using Graphics Processing Unit

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)