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Effects of Easy Hybrid Parallelization with CUDA for Numerical-Atomic-Orbital Density Functional Theory Calculation

Jae-Hyeon Parq, Erik Sevre, Sang-Mook Lee

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Tags: Computer science, CUDA, MPI, nVidia, nVidia Quadro 4000

February 21, 2014 by hgpu

Large-Scale Geospatial Processing on Multi-Core and Many-Core Processors: Evaluations on CPUs, GPUs and MICs

Jianting Zhang, Simin You

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Tags: Algorithms, Computer science, CUDA, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, nVidia Quadro 6000, Tesla C2050

February 19, 2014 by hgpu

Using of GPUs for cluster analysis of large data by K-means method

Natalya Litvinenko

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Tags: Algorithms, Cluster analysis, Computer science, CUDA, nVidia, nVidia GeForce GTX 660

February 19, 2014 by hgpu

Parallel algorithms for problems of cluster analysis with very large amount of data

Natalya Litvinenko

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Tags: Algorithms, Cluster analysis, Computer science, CUDA, Nearest neighbour, nVidia, nVidia GeForce GTX 660

February 19, 2014 by hgpu

A Similarity-Based Analysis Tool for Scientific Application Porting

Wei Ding

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, OpenMP, Performance, Portability, Tesla C2070, Thesis

February 17, 2014 by hgpu

Petascale elliptic solvers for anisotropic PDEs on GPU clusters

Eike Hermann Muller, Robert Scheichl, Benson Muite, Eero Vainikko

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Numerical Analysis, nVidia, Partial differential equations, PDEs, Tesla K20, Tesla M2090

February 17, 2014 by hgpu

GPU Programming with CUDA: A brief overview

Filipo Novo Mor, Plauto de Abreu Neto

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Tags: Computer science, CUDA, nVidia, Overview

February 17, 2014 by hgpu

Optimizing Performance of Stencil Code with SPL Conqueror

Alexander Grebhahn, Norbert Siegmund, Sven Apel, Sebastian Kuckuk, Christian Schmitt, Harald Kostler

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Source codes

Tags: Computer science, CUDA, Differential equations, Finite difference, Image processing, nVidia, OpenCL, Package, Partial differential equations, PDEs, Tesla K20

February 17, 2014 by hgpu

Interactive Design Exploration for Constrained Meshes

Bailin Deng, Sofien Bouaziz, Mario Deuss, Alexandre Kaspar, Yuliy Schwartzburg, Mark Pauly

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Tags: Algorithms, CAD, Computational Geometry, Computer science, CUDA, nVidia, nVidia GeForce GTX 580

February 17, 2014 by hgpu

Efficient pseudo-random number generation for monte-carlo simulations using graphic processors

Siddhant Mohanty, A K Mohanty, F Carminati

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Tags: Algorithms, Computer science, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, OpenCL, Pseudo-random number generators

February 17, 2014 by hgpu

Resolution of Linear Algebra for the Discrete Logarithm Problem using GPU and Multi-core Architectures

Hamza Jeljeli

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 680, OpenMPI, Security, Tesla M2050

February 17, 2014 by hgpu

Application of the Characteristic Basis Function Method using CUDA

Juan Ignacio Perez, Eliseo Garcia, Jose A. de Frutos, Felipe Catedra

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Tags: Computer science, CUDA, CULA, nVidia, Tesla C2075

February 16, 2014 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Effects of Easy Hybrid Parallelization with CUDA for Numerical-Atomic-Orbital Density Functional Theory Calculation

Large-Scale Geospatial Processing on Multi-Core and Many-Core Processors: Evaluations on CPUs, GPUs and MICs

Using of GPUs for cluster analysis of large data by K-means method

Parallel algorithms for problems of cluster analysis with very large amount of data

A Similarity-Based Analysis Tool for Scientific Application Porting

Petascale elliptic solvers for anisotropic PDEs on GPU clusters

GPU Programming with CUDA: A brief overview

Optimizing Performance of Stencil Code with SPL Conqueror

Interactive Design Exploration for Constrained Meshes

Efficient pseudo-random number generation for monte-carlo simulations using graphic processors

Resolution of Linear Algebra for the Discrete Logarithm Problem using GPU and Multi-core Architectures

Application of the Characteristic Basis Function Method using CUDA

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

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

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