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Parallel Sparse Linear Algebra for Multi-core and Many-core Platforms: Parallel Solvers and Preconditioners

Dimitar Lukarski

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Tags: Algorithms, Computer science, CUDA, Differential equations, Factorization, FEM, Finite difference, Finite element method, Linear Algebra, nVidia, nVidia GeForce GTX 580, Partial differential equations, PDEs, Sparse matrix, Tesla M1060, Tesla S1070, Thesis

March 16, 2012 by hgpu

Multi-platform Linear Algebra

E. Ketelaer, D. Lukarski

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Tags: Computer science, CUDA, Differential equations, Distributed data structures, Linear Algebra, nVidia, Package, Partial differential equations, PDEs

March 16, 2012 by hgpu

Image segmentation using CUDA implementations of the Runge-Kutta-Merson and GMRES methods

Tomas Oberhuber, Atsushi Suzuki, Jan Vacata, Vitezslav Zabka

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Tags: Algorithms, CUDA, Differential equations, Image processing, MRI, nVidia, nVidia GeForce GTX 480, ODEs, Ordinary differential equations, Partial differential equations, PDEs

February 22, 2012 by hgpu

Parallel Semi-Implicit Time Integrators

B. Ong, A. Melfi, A. Christlieb

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Partial differential equations, PDEs, Tesla C1060

February 9, 2012 by hgpu

Scientific Computation on Graphics Processing Unit using CUDA

Pradip Narendrakumar Panchal

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Tags: Computer science, CUDA, Differential equations, FDTD, Finite difference, Finite-difference time-domain, Fluid dynamics, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce GTX 280, Partial differential equations, PDEs, Thesis

January 23, 2012 by hgpu

Numerical solution of PDEs with hybrid and heterogeneous computing models

Markus Hegland

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Tags: Algorithms, CUDA, Differential equations, Fluid dynamics, Heterogeneous systems, nVidia, nVidia GeForce GTX 295, Partial differential equations, PDEs, Physics, Plasma physics, Review

December 23, 2011 by hgpu

Multi-Science Applications with Single Codebase – GAMER – for Massively Parallel Architectures

Hemant Shukla, Hsi-Yu Schive, Tak-Pong Woo, Tzihong Chiueh

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Tags: Algorithms, Astrophysics, Benchmarking, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Physics, Rendering, Tesla C2050

December 10, 2011 by hgpu

Playdoh: A lightweight Python library for distributed computing and optimisation

Cyrille Rossant, Bertrand Fontaine, Dan F.M. Goodman

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Tags: Computer science, CUDA, Differential equations, Distributed computing, Monte Carlo simulation, nVidia, nVidia GeForce GTX 295, Package, Partial differential equations, PDEs, Python

December 10, 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

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

GPU Acceleration of Solving Parabolic Partial Differential Equations Using Difference Equations

David L. Foster

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Tags: Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 480, Optimization, Partial differential equations, PDEs, Tesla C1060

December 1, 2011 by hgpu

GPU Accelerated Numerical Solutions to Chaotic PDEs

J.R. Seaton, J.C Sprott

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Tags: Algorithms, Chaotic Dynamics, Differential equations, Nonlinear Sciences, nVidia, Partial differential equations, PDEs, Physics, Tesla C870

December 1, 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

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high performance computing on graphics processing units: hgpu.org

Parallel Sparse Linear Algebra for Multi-core and Many-core Platforms: Parallel Solvers and Preconditioners

Multi-platform Linear Algebra

Image segmentation using CUDA implementations of the Runge-Kutta-Merson and GMRES methods

Parallel Semi-Implicit Time Integrators

Scientific Computation on Graphics Processing Unit using CUDA

Numerical solution of PDEs with hybrid and heterogeneous computing models

Multi-Science Applications with Single Codebase – GAMER – for Massively Parallel Architectures

Playdoh: A lightweight Python library for distributed computing and optimisation

Performance of PETSc GPU Implementation with Sparse Matrix Storage Schemes

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

GPU Acceleration of Solving Parabolic Partial Differential Equations Using Difference Equations

GPU Accelerated Numerical Solutions to Chaotic PDEs

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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

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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