high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

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

Towards a Performance-Portable FFT Library for Heterogeneous Computing

Carlo del Mundo, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 6970, ATI Radeon HD 7970, FFT, nVidia, OpenCL, Signal processing, Spectral methods, Tesla C2075, Tesla K20

February 17, 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

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

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

Towards a Performance-Portable FFT Library for Heterogeneous Computing

A Similarity-Based Analysis Tool for Scientific Application Porting

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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