high performance computing on graphics processing units: hgpu.org

hgpu.org » Matrix multiplication

Fast Conjugate Gradients with Multiple GPUs

Ali Cevahir, Akira Nukada, Satoshi Matsuoka

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Tags: Computer science, Conjugate gradient solver, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 8800 GTS

November 27, 2010 by hgpu

A Note on Auto-tuning GEMM for GPUs

Yinan Li, Jack Dongarra, Stanimire Tomov

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 280

November 27, 2010 by hgpu

Numerical linear algebra on emerging architectures: The PLASMA and MAGMA projects

Emmanuel Agullo, Jim Demmel, Jack Dongarra, Bilel Hadri, Jakub Kurzak, Julien Langou, Hatem Ltaief, Piotr Luszczek, Stanimire Tomov

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Tags: Algorithms, Computer science, Linear Algebra, Matrix multiplication

November 27, 2010 by hgpu

Molecular structural mechanics approach to carbon nanotubes on graphics processing units

Xia Jian-ming, Wei De-min

Tags: Matrix multiplication, Molecular modeling, Physics

November 25, 2010 by hgpu

Fast matrix multiplies using graphics hardware

E. Scott Larsen, David Mcallister

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Tags: Computer science, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 3, OpenGL

November 24, 2010 by hgpu

Power Efficient Large Matrices Multiplication by Load Scheduling on Multi-core and GPU Platform with CUDA

DaQi Ren, Reiji Suda

Tags: Computer science, CUDA, Energy-efficient computing, Matrix multiplication, nVidia

November 8, 2010 by hgpu

Solving Path Problems on the GPU

Aydin Buluc, John R. Gilbert, Ceren Budak

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce 8800 Ultra, Package, Path problems

November 5, 2010 by hgpu

Faster matrix-vector multiplication on GeForce 8800GTX

N. Fujimoto

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 8800 GTX

November 5, 2010 by hgpu

Quantum Monte Carlo on graphical processing units

A. Anderson, W. Goddard, P. Schroder

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Tags: Computational Physics, Floating point error, Matrix multiplication, Monte Carlo simulation, nVidia GeForce 7800 GTX, Physics

November 3, 2010 by hgpu

Improving Performance of Matrix Multiplication and FFT on GPU

Xiang Cui, Yifeng Chen, Hong Mei

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Tags: Computer science, CUDA, FFT, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 280

November 2, 2010 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

Fast Conjugate Gradients with Multiple GPUs

A Note on Auto-tuning GEMM for GPUs

Numerical linear algebra on emerging architectures: The PLASMA and MAGMA projects

Molecular structural mechanics approach to carbon nanotubes on graphics processing units

Fast matrix multiplies using graphics hardware

Power Efficient Large Matrices Multiplication by Load Scheduling on Multi-core and GPU Platform with CUDA

Solving Path Problems on the GPU

Faster matrix-vector multiplication on GeForce 8800GTX

Quantum Monte Carlo on graphical processing units

Improving Performance of Matrix Multiplication and FFT on GPU

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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