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Topology Optimization with Unstructured Meshes on Graphics Processing Units (GPUs)

Tomas Zegard Latrach

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, Optimization, Tesla T10, Thesis

November 3, 2011 by hgpu

Efficient Quicksort and 2D Convex Hull for CUDA, and MSIMD as a Realistic Model of Massively Parallel Computations

Tomasz Jurkiewicz, Piotr Danilewski

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Sorting

November 3, 2011 by hgpu

A Comparison of Many-threaded Differential Evolution and Genetic Algorithms on CUDA

Pavel Kromer, Jan Platos, Vaclav Snasel, Ajith Abraham

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Tags: Algorithms, Computer science, CUDA, Differential evolution, Genetic programming, Metaheuristics, nVidia, Task scheduling, Tesla C2050

November 2, 2011 by hgpu

Hybrid GPU-CPU Adaptive Precision Ray-Triangle Intersection Tests for Robust High-Performance GPU Dosimetry Computations

Lancelot Perrotte, Bruno Bodin, Laurent Chodorge

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Tags: Algorithms, CUDA, Floating point error, Nuclear physics, nVidia, nVidia GeForce GTX 295, Physics, Raytracing

November 2, 2011 by hgpu

Finite Volume Errors in B_K

Jangho Kim, Hyung-Jin Kim, Weonjong Lee, Chulwoo Jung, Stephen R. Sharpe

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Tags: CUDA, High Energy Physics - Lattice, nVidia, nVidia GeForce GTX 480, Physics

November 2, 2011 by hgpu

Multi GPU Performance of Conjugate Gradient Solver with Staggered Fermions in Mixed Precision

Yong-Chull Jang, Hyung-Jin Kim, Weonjong Lee

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Tags: Algorithms, Cg, Computational Physics, Conjugate gradient solver, CUDA, High Energy Physics - Lattice, Mixed precision, nVidia, nVidia GeForce GTX 480, Physics

November 2, 2011 by hgpu

APHOG: A Framework for Fast Object Detection Using Histograms of Oriented Gradients

Chris Cowdery-Corvan, Liangyi Fan, Thomas Knack

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Tags: Computer science, Computer vision, CUDA, nVidia

November 1, 2011 by hgpu

Exploring Fine-Grained Task-based Execution on Multi-GPU Systems

Long Chen, Oreste Villa, Guang R. Gao

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Tags: Computer science, CUDA, GPU cluster, Molecular dynamics, nVidia, Tesla C1060

November 1, 2011 by hgpu

Using DRBL to Deploy MPICH2 and CUDA on Green Computing

Wu Jiun-Yu, Wang Yao-Tsung, Shiau Steven, Wang Hui Ching

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Tags: Computer science, CUDA, Energy-efficient computing, Green, nVidia, nVidia GeForce 9800 GT

November 1, 2011 by hgpu

Quantum chemical many-body theory on heterogeneous nodes

A. Eugene DePrince, Jeff R. Hammond

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Tags: Algorithms, Computational chemistry, CUBLAS, CUDA, Heterogeneous systems, nVidia, Presentation, Tesla C1060, Tesla C2050

November 1, 2011 by hgpu

An Implementation of Differential Evolution for Independent Tasks Scheduling on GPU

Pavel Kromer, Jan Platos, Vaclav Snasel, Ajith Abraham

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Differential evolution, Heterogeneous systems, nVidia, Optimization, Task scheduling, Tesla C2050

November 1, 2011 by hgpu

Fast computation of scattering maps of nanostructures using graphical processing units

Vincent Favre-Nicolin, Johann Coraux, Marie-Ingrid Richard, Hubert Renevier

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Source codes

Tags: Condensed matter, CUDA, Materials Science, Mesoscale and Nanoscale Physics, nVidia, nVidia GeForce GTX 295, Package, Python

November 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

Topology Optimization with Unstructured Meshes on Graphics Processing Units (GPUs)

Efficient Quicksort and 2D Convex Hull for CUDA, and MSIMD as a Realistic Model of Massively Parallel Computations

A Comparison of Many-threaded Differential Evolution and Genetic Algorithms on CUDA

Hybrid GPU-CPU Adaptive Precision Ray-Triangle Intersection Tests for Robust High-Performance GPU Dosimetry Computations

Finite Volume Errors in B_K

Multi GPU Performance of Conjugate Gradient Solver with Staggered Fermions in Mixed Precision

APHOG: A Framework for Fast Object Detection Using Histograms of Oriented Gradients

Exploring Fine-Grained Task-based Execution on Multi-GPU Systems

Using DRBL to Deploy MPICH2 and CUDA on Green Computing

Quantum chemical many-body theory on heterogeneous nodes

An Implementation of Differential Evolution for Independent Tasks Scheduling on GPU

Fast computation of scattering maps of nanostructures using graphical processing units

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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