high performance computing on graphics processing units: hgpu.org

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Large-Scale Paralleled Sparse Principal Component Analysis

W. Liu, H. Zhang, D. Tao, Y. Wang, K. Lu

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Tags: Computer science, CUBLAS, CUDA, Machine learning, Numerical Analysis, nVidia, Tesla C2050

December 24, 2013 by hgpu

Resource Centered Computing delivering high parallel performance

Jens Gustedt, Stephane Vialle, Patrick Mercier

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Tags: Computer science, CUBLAS, CUDA, GPU cluster, Hierarchical clustering, MPI, nVidia, nVidia GeForce GTX 580

December 22, 2013 by hgpu

Efficient Heterogeneous Execution on Large Multicore and Accelerator Platforms: Case Study Using a Block Tridiagonal Solver

Alfred J. Park, Kalyan S. Perumalla

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Tags: Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Tesla X2090

August 20, 2013 by hgpu

GPU Implementation of the DP code

F. Sottile, C. Roedl, V. Slavnic, P. Jovanovic, D. Stankovic, P. Kestener, F. Houssen

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Tags: Computer science, CUBLAS, CUDA, nVidia, Tesla M2090

June 23, 2013 by hgpu

Making the case of GPUs in courses on computational physics

Knut Skogstrand Gjerden

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Tags: Computational Physics, CUBLAS, CUDA, Education, FFT, Mathematical Software, nVidia, nVidia GeForce GTX 320 M, Physics, Tesla C2050

May 17, 2013 by hgpu

Optimizing CUDA Code By Kernel Fusion – Application on BLAS

Jiri Filipovic, Matus Madzin, Jan Fousek, Ludek Matyska

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Tags: BLAS, Code generation, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 480

May 7, 2013 by hgpu

Batched Kronecker product for 2-D matrices and 3-D arrays on NVIDIA GPUs

Chetan Jhurani

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Tags: BLAS, CUBLAS, CUDA, Kronecker product, nVidia, Tesla K20

April 10, 2013 by chetan.jhurani

A GEMM interface and implementation on NVIDIA GPUs for multiple small matrices

Chetan Jhurani, Paul Mullowney

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Tags: BLAS, CUBLAS, CUDA, Dense linear algebra, GEMM, Linear Algebra, nVidia, Parallel programming, Tesla K20

April 9, 2013 by chetan.jhurani

Accelerated Dictionary Learning with GPU/Multicore CPU and Its Application to Music Classification

Boyang Gao, Emmanuel Dellandrea, Liming Chen

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Tags: Clustering, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 285, Signal processing

March 26, 2013 by hgpu

Hyperspectral Unmixing on GPUs and Multi-Core Processors: A Comparison

Sergio Bernabe, Sergio Sanchez, Antonio Plaza, Sebastian Lopez, Jon Atli Benediktsson, Roberto Sarmiento

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Tags: Algorithms, CUBLAS, CUDA, Image processing, nVidia, nVidia GeForce GTX 580, Tesla C1060

March 26, 2013 by hgpu

Performance Upper Bound Analysis and Optimization of SGEMM on Fermi and Kepler GPUs

Junjie Lai, Andre Seznec

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Tags: Algorithms, Benchmarking, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 680, Optimization, Performance

February 22, 2013 by hgpu

Autotuning, Code Generation and Optimizing Compiler Technology for GPUs

Malik Muhammad Zaki Murtaza Khan

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Tags: Code generation, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C2050, Thesis

January 26, 2013 by hgpu

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

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high performance computing on graphics processing units: hgpu.org

Large-Scale Paralleled Sparse Principal Component Analysis

Resource Centered Computing delivering high parallel performance

Efficient Heterogeneous Execution on Large Multicore and Accelerator Platforms: Case Study Using a Block Tridiagonal Solver

GPU Implementation of the DP code

Making the case of GPUs in courses on computational physics

Optimizing CUDA Code By Kernel Fusion – Application on BLAS

Batched Kronecker product for 2-D matrices and 3-D arrays on NVIDIA GPUs

A GEMM interface and implementation on NVIDIA GPUs for multiple small matrices

Accelerated Dictionary Learning with GPU/Multicore CPU and Its Application to Music Classification

Hyperspectral Unmixing on GPUs and Multi-Core Processors: A Comparison

Performance Upper Bound Analysis and Optimization of SGEMM on Fermi and Kepler GPUs

Autotuning, Code Generation and Optimizing Compiler Technology for GPUs

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

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