high performance computing on graphics processing units: hgpu.org

hgpu.org » Linear Algebra

From Sparse Matrix to Optimal GPU CUDA Sparse Matrix Vector Product Implementation

Ahmed H. El Zein, Alistair P. Rendell

Tags: Computer science, CUDA, Linear Algebra, nVidia, Performance, Sparse matrix

May 20, 2011 by hgpu

GPU-PRISM: An Extension of PRISM for General Purpose Graphics Processing Units

Dragan Bosnacki, Stefan Edelkamp, Damian Sulewski, Anton Wijs

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, Probabilistic model checking

May 19, 2011 by hgpu

Iterative SLE Solvers over a CPU-GPU Platform

Alecio P.D. Binotto, Christian Daniel, Daniel Weber, Arjan Kuijper, Andre Stork, Carlos Pereira, Dieter Fellner

Tags: Algorithms, Fluid dynamics, Heterogeneous systems, Linear Algebra

May 14, 2011 by hgpu

Sparse Matrix Formats Evaluation and Optimization on a GPU

Maxime R. Hugues, Serge G. Petiton

Tags: Computer science, Linear Algebra, Sparse matrix

May 1, 2011 by hgpu

Optimized HPL for AMD GPU and multi-core CPU usage

Matthias Bach, Matthias Kretz, Volker Lindenstruth, David Rohr

Tags: ATI, ATI Radeon HD 5870, Computer science, GPU cluster, Heterogeneous systems, Linear Algebra, MPI, Performance

April 25, 2011 by hgpu

Pretty Good Accuracy in Matrix Multiplication with GPUs

Matthew Badin, Lubomir Bic, Michael Dillencourt, Alexandru Nicolau

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 285

April 21, 2011 by hgpu

Using graphics processors to accelerate the computation of the matrix inverse

P. Ezzatti, E. Quintana-Orti, A. Remon

Source codes

Tags: Computer science, Linear Algebra, Matrix inversion

April 21, 2011 by hgpu

Automatically generating and tuning GPU code for sparse matrix-vector multiplication from a high-level representation

Dominik Grewe, Anton Lokhmotov

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Tags: ATI, ATI Radeon HD 5970, Code generation, Computer science, CUDA, High-level Languages, Linear Algebra, nVidia, OpenCL, Sparse matrix, Tesla S1070

April 21, 2011 by hgpu

Auto-Tuning CUDA Parameters for Sparse Matrix-Vector Multiplication on GPUs

Ping Guo, Liqiang Wang

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce 9500 GTX, nVidia GeForce GTX 295, Sparse matrix

April 21, 2011 by hgpu

Accelerating Linpack Performance with Mixed Precision Algorithm on CPU+GPGPU Heterogeneous Cluster

Wang Lei, Zhang Yunquan, Zhang Xianyi, Liu Fangfang

Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, Linear Algebra, Mixed precision, nVidia, nVidia GeForce GTX 295, Tesla C1060

April 20, 2011 by hgpu

Implementation of Jacobi iterative method on graphics processor unit

Tao Wang, Yuan Yao, Lin Han, Dan Zhang, Yuanyuan Zhang

Tags: Computer science, CUDA, Linear Algebra, nVidia

April 15, 2011 by hgpu

CULA: hybrid GPU accelerated linear algebra routines

John R. Humphrey, Daniel K. Price, Kyle E. Spagnoli, Aaron L. Paolini, Eric J. Kelmelis

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Source codes

Tags: Computer science, CUDA, CULA, Linear Algebra, nVidia, Package, Tesla C1060

April 11, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

From Sparse Matrix to Optimal GPU CUDA Sparse Matrix Vector Product Implementation

GPU-PRISM: An Extension of PRISM for General Purpose Graphics Processing Units

Iterative SLE Solvers over a CPU-GPU Platform

Sparse Matrix Formats Evaluation and Optimization on a GPU

Optimized HPL for AMD GPU and multi-core CPU usage

Pretty Good Accuracy in Matrix Multiplication with GPUs

Using graphics processors to accelerate the computation of the matrix inverse

Automatically generating and tuning GPU code for sparse matrix-vector multiplication from a high-level representation

Auto-Tuning CUDA Parameters for Sparse Matrix-Vector Multiplication on GPUs

Accelerating Linpack Performance with Mixed Precision Algorithm on CPU+GPGPU Heterogeneous Cluster

Implementation of Jacobi iterative method on graphics processor unit

CULA: hybrid GPU accelerated linear algebra routines

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

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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