high performance computing on graphics processing units: hgpu.org

hgpu.org » Linear Algebra

Fast development of dense linear algebra codes on graphics processors

M. Jesus Zafont, Alberto F. Martin, Francisco Igual, Enrique S. Quintana-Orti

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce 8800 Ultra

January 20, 2011 by hgpu

Solving dense linear systems on platforms with multiple hardware accelerators

Enrique S. Quintana-Orti, Francisco D. Igual, Enrique S. Quintana-Orti, Robert A. van de Geijn

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Source codes

Tags: Computer science, CUDA, GPU cluster, Linear Algebra, nVidia, Package, Task scheduling, Tesla S870

January 17, 2011 by hgpu

Accelerating linpack with CUDA on heterogenous clusters

Massimiliano Fatica

Tags: Computer science, CUDA, GPU cluster, Linear Algebra, nVidia

January 11, 2011 by hgpu

Evaluation and tuning of the Level 3 CUBLAS for graphics processors

S. Barrachina, M. Castillo, F. D. Igual, R. Mayo, E. S. Quintana-Orti

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce 8800 Ultra

January 9, 2011 by hgpu

A complete modular resultant algorithm targeted for realization on graphics hardware

Pavel Emeliyanenko

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280

January 5, 2011 by hgpu

Modular Resultant Algorithm for Graphics Processors

Pavel Emeliyanenko

Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280

January 5, 2011 by hgpu

Efficient Multiplication of Polynomials on Graphics Hardware

Pavel Emeliyanenko

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Tags: Computer science, CUDA, Linear Algebra, nVidia

January 4, 2011 by hgpu

GPU based sparse grid technique for solving multidimensional options pricing PDEs

Abhijeet Gaikwad, Ioane Muni Toke

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Tags: Computational finance, CUDA, Finance, Linear Algebra, nVidia, Sparse matrix, Tesla C870

December 28, 2010 by hgpu

Generating subdivision curves with L-systems on a GPU

Radomir Mech, Przemyslaw Prusinkiewicz

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Tags: Algorithms, ATI, ATI CTM, ATI Radeon 9700, Computer science, Linear Algebra

December 28, 2010 by hgpu

Performance Study of LU Decomposition on the Programmable GPU

Fumihiko Ino, Manabu Matsui, Keigo Goda, Kenichi Hagihara

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Tags: Cg, Computer science, Linear Algebra, nVidia, nVidia GeForce FX 5900 Ultra, nVidia Quadro FX 3400, OpenGL

December 26, 2010 by hgpu

Using Hybrid CPU-GPU Platforms to Accelerate the Computation of the Matrix Sign Function

Peter Benner, Pablo Ezzatti, Enrique S. Quintana-Orti, Alfredo Remon

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, Tesla C1060

December 25, 2010 by hgpu

Singular value decomposition on GPU using CUDA

Sheetal Lahabar, P. J. Narayanan

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Tags: Computer science, Linear Algebra, nVidia, nVidia GeForce GTX 280, Tesla S1070

December 24, 2010 by hgpu

Over-synchronization in GPU Programs

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

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See all packages

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high performance computing on graphics processing units: hgpu.org

Fast development of dense linear algebra codes on graphics processors

Solving dense linear systems on platforms with multiple hardware accelerators

Accelerating linpack with CUDA on heterogenous clusters

Evaluation and tuning of the Level 3 CUBLAS for graphics processors

A complete modular resultant algorithm targeted for realization on graphics hardware

Modular Resultant Algorithm for Graphics Processors

Efficient Multiplication of Polynomials on Graphics Hardware

GPU based sparse grid technique for solving multidimensional options pricing PDEs

Generating subdivision curves with L-systems on a GPU

Performance Study of LU Decomposition on the Programmable GPU

Using Hybrid CPU-GPU Platforms to Accelerate the Computation of the Matrix Sign Function

Singular value decomposition on GPU using CUDA

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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

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