high performance computing on graphics processing units: hgpu.org

hgpu.org » Sparse matrix

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

Performance of PETSc GPU Implementation with Sparse Matrix Storage Schemes

Pramod Kumbhar

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Tags: ATI, ATI FireStream, Computer science, CUDA, Differential equations, GPU cluster, nVidia, OpenCL, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Thesis

December 8, 2011 by hgpu

Sparse-Matrix-CG-Solver in CUDA

Dominik Michels

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Tags: Algorithms, Computer science, Conjugate gradient solver, CUDA, nVidia, nVidia GeForce GTX 480, Sparse matrix

December 7, 2011 by hgpu

Towards a complete FEM-based simulation toolkit on GPUs: Geometric Multigrid solvers

Markus Geveler, Dirk Ribbrock, Dominik Goddeke, Peter Zajac, Stefan Turek

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Tags: Benchmarking, CUDA, Differential equations, FEM, Finite element method, Fluid dynamics, nVidia, nVidia GeForce GTX 285, Partial differential equations, PDEs, Sparse matrix

December 7, 2011 by hgpu

Parallel GMRES implementation for solving sparse linear systems on GPU clusters

Jacques M. Bahi, Raphael Couturier, Lilia Ziane Khodja

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

November 25, 2011 by hgpu

A new approach for sparse matrix vector product on NVIDIA GPUs

F. Vazquez, J. J. Fernandez, E. M. Garzon

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Optimization, Sparse matrix

November 21, 2011 by hgpu

A Memory Efficient and Fast Sparse Matrix Vector Product on a GPU

A. Dziekonski, A. Lamecki, M. Mrozowski

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Tags: Computer science, CUDA, Electrodynamics, FEM, Finite element method, nVidia, nVidia GeForce GTX 480, Performance, Sparse matrix

October 26, 2011 by hgpu

Multifrontal computations on GPUs and their multi-core hosts

Robert F. Lucas, Gene Wagenbreth, Dan M. Davis, Roger Grimes

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

October 7, 2011 by hgpu

Investigation on the Use of GPGPU for Fast Sparse Matrix Factorization

Ye Tian, Bin Zhou, Yutong Zhang, Ka Wing Chan

Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, Sparse matrix

October 7, 2011 by hgpu

A model-driven partitioning and auto-tuning integrated framework for sparse matrix-vector multiplication on GPUs

Ping Guo, He Huang, Qichang Chen, Liqiang Wang, En-Jui Lee, Po Chen

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Performance, Software Engineering, Sparse matrix

September 19, 2011 by hgpu

A Fast GPU Implementation for Solving Sparse Ill-Posed Linear Equation Systems

Florian Stock, Andreas Koch

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Tags: Cell processor, Conjugate gradient solver, CUDA, FPGA, Image processing, Image reconstruction, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 280, Optimization, Sparse matrix

September 8, 2011 by hgpu

Parallel implementation of conjugate gradient method on graphics processors

Marcin Wozniak, Tomasz Olas, Roman Wyrzykowski

Tags: Algorithms, Computer science, Conjugate gradient solver, CUDA, nVidia, nVidia GeForce 8800 GTX, Optimization, Sparse matrix, Tesla C1060

September 7, 2011 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

GPU-Accelerated Preconditioned Iterative Linear Solvers

Performance of PETSc GPU Implementation with Sparse Matrix Storage Schemes

Sparse-Matrix-CG-Solver in CUDA

Towards a complete FEM-based simulation toolkit on GPUs: Geometric Multigrid solvers

Parallel GMRES implementation for solving sparse linear systems on GPU clusters

A new approach for sparse matrix vector product on NVIDIA GPUs

A Memory Efficient and Fast Sparse Matrix Vector Product on a GPU

Multifrontal computations on GPUs and their multi-core hosts

Investigation on the Use of GPGPU for Fast Sparse Matrix Factorization

A model-driven partitioning and auto-tuning integrated framework for sparse matrix-vector multiplication on GPUs

A Fast GPU Implementation for Solving Sparse Ill-Posed Linear Equation Systems

Parallel implementation of conjugate gradient method on graphics processors

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