high performance computing on graphics processing units: hgpu.org

hgpu.org » Sparse matrix

New Row-grouped CSR format for storing the sparse matrices on GPU with implementation in CUDA

Tomas Oberhuber, Atsushi Suzuki, Jan Vacata

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

December 13, 2010 by hgpu

Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy

Alfredo Buttari, Jack Dongarra, Jakub Kurzak, Piotr Luszczek, Stanimir Tomov

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Tags: Algorithms, Computer science, Linear Algebra, Mixed precision, Sparse matrix

December 12, 2010 by hgpu

Solving Sparse Linear Systems on NVIDIA Tesla GPUs

Mingliang Wang, Hector Klie, Manish Parashar, Hari Sudan

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Sparse matrix, Tesla T10P

November 27, 2010 by hgpu

Exact Sparse Matrix-Vector Multiplication on GPU’s and Multicore Architectures

Brice Boyer, Jean-Guillaume Dumas, Pascal Giorgi

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Tags: Computer science, CUDA, Mathematical Software, nVidia, nVidia GeForce GTX 280, OpenMP, Package, Sparse matrix, Symbolic Computation

November 11, 2010 by hgpu

Parallel Sparse Matrix Solver on the GPU Applied to Simulation of Electrical Machines

Antonio Wendell De Oliveira Rodrigues, Frederic Guyomarch, Yvonnick Le Menach, Jean-Luc Dekeyser

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Tags: Computer science, Conjugate gradient solver, CUDA, nVidia, nVidia GeForce GTX 280, Sparse matrix, Tesla C870

November 9, 2010 by hgpu

A matrix approach to tomographic reconstruction and its implementation on GPUs

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

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Tags: Biology, Image processing, Sparse matrix

November 6, 2010 by hgpu

The GPU as numerical simulation engine

J. Bolz, I. Farmer, E. Grinspun, P. Schroder

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Tags: Computer science, Fluid simulation, Navier-Stokes equations, NSEs, Numerical simulation, nVidia, Sparse matrix

November 5, 2010 by hgpu

Sparse matrix solvers on the GPU: conjugate gradients and multigrid

Jeff Bolz,Ian Farmer,Eitan Grinspun,Peter Schrooder

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Tags: Computer science, Fluid simulation, Navier-Stokes equations, NSEs, Numerical simulation, nVidia, Sparse matrix

November 5, 2010 by hgpu

Implementing sparse matrix-vector multiplication on throughput-oriented processors

Nathan Bell, Michael Garland

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, Package, Sparse matrix

November 4, 2010 by hgpu

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Clava: C/C++ Source-to-Source Tool based on Clang

Challenges and Opportunities in C/C++ Source-To-Source Compilation

gpuLik

Statistical Computing With Graphics Processing Units

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

BAT: A standardized benchmark suite for auto-tuners

Towards a Benchmarking Suite for Kernel Tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

EvoTorch: Scalable Evolutionary Computation in Python

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

See all packages

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high performance computing on graphics processing units: hgpu.org

New Row-grouped CSR format for storing the sparse matrices on GPU with implementation in CUDA

Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy

Solving Sparse Linear Systems on NVIDIA Tesla GPUs

Exact Sparse Matrix-Vector Multiplication on GPU’s and Multicore Architectures

Parallel Sparse Matrix Solver on the GPU Applied to Simulation of Electrical Machines

A matrix approach to tomographic reconstruction and its implementation on GPUs

The GPU as numerical simulation engine

Sparse matrix solvers on the GPU: conjugate gradients and multigrid

Implementing sparse matrix-vector multiplication on throughput-oriented processors

Recent source codes

Clava: C/C++ Source-to-Source Tool based on Clang

gpuLik

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

BAT: A standardized benchmark suite for auto-tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

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