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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

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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high performance computing on graphics processing units: hgpu.org

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

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

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