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Parallel Spectral Graph Partitioning on CUDA

Orhan Firat, Alptekin Temizel

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Tags: Algorithms, CUDA, Image processing, Machine learning, nVidia, Tesla C2070

February 23, 2014 by hgpu

Fast Boolean Calculations Using the GPU

Bernd Steinbach, Matthias Werner

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Tags: Computer science, CUDA, nVidia, Tesla C2070

February 21, 2014 by hgpu

Performance Impact of Data Layout on the GPU-accelerated IDW Interpolation

Gang Mei, Hong Tian

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 640

February 21, 2014 by hgpu

Computing least squares condition numbers on hybrid multicore/GPU systems

Marc Baboulin, Jack Dongarra, Remi Lacroix

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Tesla C2075

February 21, 2014 by hgpu

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

X-ray CT on the GPU

Ravikiran Tadepalli

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Tags: Algorithms, CUDA, Medicine, nVidia, Tesla C1060, Thesis, Tomography

February 19, 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

Fast Hamiltonian Monte Carlo Using GPU Computing

Andrew L. Beam, Sujit K. Ghosh, Jon Doyle

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Source codes

Tags: Algorithms, Bayesian, CUDA, CULA, Monte Carlo simulation, nVidia, Package, Python, Statistics, Tesla K20

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

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Parallel Spectral Graph Partitioning on CUDA

Fast Boolean Calculations Using the GPU

Performance Impact of Data Layout on the GPU-accelerated IDW Interpolation

Computing least squares condition numbers on hybrid multicore/GPU systems

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

X-ray CT on the GPU

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

Fast Hamiltonian Monte Carlo Using GPU Computing

A Similarity-Based Analysis Tool for Scientific Application Porting

Petascale elliptic solvers for anisotropic PDEs on GPU clusters

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Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

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