high performance computing on graphics processing units: hgpu.org

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Multifrontal Sparse Matrix Factorization on Graphics Processing Units

Robert F. Lucas, Gene Wagenbreth, John J. Tran, Dan M. Davis

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Tags: Computer science, CUDA, Factorization, nVidia, nVidia GeForce 8800, Sparse matrix

January 25, 2012 by hgpu

Incomplete-LU and Cholesky Preconditioned Iterative Methods Using CUSPARSE and CUBLAS

Maxim Naumov

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, Linear Algebra, nVidia, Tesla C2050

January 12, 2012 by hgpu

LU Factorization for Accelerator-based Systems

Emmanuel Agullo, Cedric Augonnet, Jack Dongarra, Mathieu Faverge, Julien Langou, Hatem Ltaief, Stanimire Tomov

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Tesla S1070, Tesla S2050

January 9, 2012 by hgpu

A class of communication-avoiding algorithms for solving general dense linear systems on CPU/GPU parallel machines

Marc Baboulin, Simplice Donfack, Laura Grigori, Adrien Remy, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Performance, Tesla S2050

January 8, 2012 by hgpu

A Highly Efficient GPU-CPU Hybrid Parallel Implementation of Sparse LU Factorization

Liu Li, Liu Li, Yang Guangwen

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

January 8, 2012 by hgpu

Multifrontal Factorization of Sparse SPD Matrices on GPUs

Thomas George, Vaibhav Saxena, Anshul Gupta, Amik Singh, Anamitra R. Choudhury

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Tags: Computer science, CUDA, Factorization, nVidia, Sparse matrix, Tesla S1070

December 26, 2011 by hgpu

Accelerating linear system solutions using randomization techniques

Marc Baboulin, Jack Dongarra, Julien Herrmann, Stanimire Tomov

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Tags: Computer science, CUDA, Factorization, Linear Algebra, nVidia, Tesla C2050

December 25, 2011 by hgpu

GPU-Accelerated Preconditioned Iterative Linear Solvers

Ruipeng Li, Yousef Saad

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Tags: Computer science, Conjugate gradient solver, CUDA, Factorization, Linear Algebra, nVidia, Overview, Sparse matrix, Tesla C1060

December 19, 2011 by hgpu

A Predictive Model for Solving Small Linear Algebra Problems in GPU Registers

Michael J. Anderson, David Sheffield, Kurt Keutzer

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Source codes

Tags: Benchmarking, Computer science, CUDA, Factorization, Linear Algebra, nVidia, nVidia Quadro FX 6000, Package, Signal processing

December 16, 2011 by hgpu

GPU Algorithms for the Estimation of Environmental Models Based on Large Datasets

Francesco Finazzi, Michela Cameletti

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Tags: Algorithms, CUDA, Earth and Space Sciences, Factorization, nVidia, Tesla C1060

December 15, 2011 by hgpu

Toward Accelerating the Matrix Inversion Computation of Symmetric Positive-Definite Matrices on Heterogeneous GPU-Based Systems

Huda Ibeid, Dinesh Kaushik, David Keyes, Hatem Ltaief

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, Matrix inversion, nVidia, Tesla C2070

December 14, 2011 by hgpu

Enhanced Parallel ILU (p)-based Preconditioners for Multi-core CPUs and GPUs-The Power (g)-pattern Method

Vincent Heuveline, Dimitar Lukarski, Jan-Philipp Weiss

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Tags: Computer science, CUDA, Factorization, Numerical simulation, nVidia, Tesla S1070

December 9, 2011 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

Multifrontal Sparse Matrix Factorization on Graphics Processing Units

Incomplete-LU and Cholesky Preconditioned Iterative Methods Using CUSPARSE and CUBLAS

LU Factorization for Accelerator-based Systems

A class of communication-avoiding algorithms for solving general dense linear systems on CPU/GPU parallel machines

A Highly Efficient GPU-CPU Hybrid Parallel Implementation of Sparse LU Factorization

Multifrontal Factorization of Sparse SPD Matrices on GPUs

Accelerating linear system solutions using randomization techniques

GPU-Accelerated Preconditioned Iterative Linear Solvers

A Predictive Model for Solving Small Linear Algebra Problems in GPU Registers

GPU Algorithms for the Estimation of Environmental Models Based on Large Datasets

Toward Accelerating the Matrix Inversion Computation of Symmetric Positive-Definite Matrices on Heterogeneous GPU-Based Systems

Enhanced Parallel ILU (p)-based Preconditioners for Multi-core CPUs and GPUs-The Power (g)-pattern Method

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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