high performance computing on graphics processing units: hgpu.org

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A GaBP-GPU Algorithm of Solving Large-Scale Sparse Linear Systems

Hanyuan Zheng, Anping Song, Zhixiang Liu, Lei Xu, Wu Zhang

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Tags: Algorithms, Computer science, CUDA, nVidia, Sparse matrix, Tesla C1060

February 25, 2014 by hgpu

Real Time Face Detection on GPU Using OpenCL

Narmada Naik, Rathna G.N.

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Tags: Algorithms, ATI, ATI Radeon HD 7670 M, Computer science, Computer vision, OpenCL

February 23, 2014 by hgpu

Accelerating Content-Based Image Retrieval via GPU-adaptive Index Structure

Zhu Lei

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Tags: Algorithms, Computer science, Computer vision, CUDA, Information Retrieval, nVidia, nVidia GeForce GTX 460

February 23, 2014 by hgpu

Multi-Elimination ILU Preconditioners on GPUs

Dimitar Lukarski, Hartwig Anzt, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Tesla K40

February 23, 2014 by hgpu

WPA/WPA2 Password Security Testing using Graphics Processing Units

Sorin Andrei Visan

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Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GT 610 M, Security

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

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

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

HiRep

Scaling SU(2) to 1000 GPUs using HiRep

Gaia AVU-GSR

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

A GaBP-GPU Algorithm of Solving Large-Scale Sparse Linear Systems

Real Time Face Detection on GPU Using OpenCL

Accelerating Content-Based Image Retrieval via GPU-adaptive Index Structure

Multi-Elimination ILU Preconditioners on GPUs

WPA/WPA2 Password Security Testing using Graphics Processing Units

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

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

Recent source codes

tdg-benchs: benchmarks used to test the performance of taskgraph

SW#SYCL

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

HiRep

Gaia AVU-GSR

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

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