high performance computing on graphics processing units: hgpu.org

hgpu.org » Matrix multiplication

A fight for performance and accuracy of the matrix multiplication routines: CUBLAS on Nvidia Tesla versus MKL and ATLAS on Intel Nehalem

Philippe Estival, Luc Giraud

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, nVidia, Tesla T10

May 29, 2012 by hgpu

Java on CUDA architecture

Jan Strnad

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Tags: Computer science, CUDA, Image processing, Java, Linear Algebra, Matrix multiplication, nVidia, Thesis

May 24, 2012 by hgpu

An Introduction to the OpenCL Programming Model

Jonathan Thompson, Kristofer Schlachter

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Tags: ATI, ATI Radeon HD 5850, ATI Radeon HD 6750 M, Computer science, Matrix multiplication, nVidia, nVidia Quadro FX 2000, OpenCL, Overview, Tutorial

May 16, 2012 by hgpu

A Heterogeneous Accelerated Matrix Multiplication: OpenCL + APU + GPU+ Fast Matrix Multiply

Paolo D'Alberto

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Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 6750, Computer science, Heterogeneous systems, Mathematical Software, Matrix multiplication, OpenCL

May 16, 2012 by hgpu

Matrix Multiplication with CUDA – A basic introduction to the CUDA programming model

Robert Hochberg

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce 9600 M GT, nVidia GeForce GT 330 M, Tesla C1060

April 27, 2012 by hgpu

Performance Exploration of Selected Manually and Automatically Parallelized Codes on GPUs

Franz Xaver Bayerl

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Tags: Code generation, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, nVidia GeForce 9800 GTX, nVidia GeForce GTX 560 Ti, Performance, Thesis

April 19, 2012 by hgpu

Algorithm Construction for GPGPU

Mattias Svanstrom, Simon Hossjer

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Tags: Algorithms, ATI, ATI Radeon HD 5650, Computer science, Matrix multiplication, nVidia, nVidia GeForce 8400 GS, nVidia GeForce GTX 560 Ti, OpenCL, Sorting

April 19, 2012 by hgpu

phiGEMM: a CPU-GPU library for porting Quantum ESPRESSO on hybrid systems

Filippo Spiga, Ivan Girotto

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Source codes

Tags: Benchmarking, BLAS, Computer science, CUDA, FFT, Matrix multiplication, nVidia, Package, Tesla C2050

April 14, 2012 by hgpu

Machine Learning for Predictive Auto-Tuning with Boosted Regression Trees

James Bergstra, Nicolas Pinto, David Cox

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Tags: Computer science, CUDA, Filtering, Machine learning, Matrix multiplication, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Optimization, Tesla C1060, Tesla C2070

March 29, 2012 by hgpu

Strassen’s Matrix Multiplication on GPUs

Junjie Li, Sanjay Ranka, Sartaj Sahni

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, Tesla C1060

January 23, 2012 by hgpu

Optimising the DBCSR GPU Implementation

Jay Chetty

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, Sparse matrix, Tesla C2050, Thesis

December 31, 2011 by hgpu

Generating SU(Nc) pure gauge lattice QCD configurations on GPUs with CUDA and OpenMP

Nuno Cardoso, Pedro Bicudo

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Tags: Computational Physics, CUDA, High Energy Physics - Lattice, Matrix multiplication, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 580, Package, Physics, QCD

December 21, 2011 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

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

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high performance computing on graphics processing units: hgpu.org

A fight for performance and accuracy of the matrix multiplication routines: CUBLAS on Nvidia Tesla versus MKL and ATLAS on Intel Nehalem

Java on CUDA architecture

An Introduction to the OpenCL Programming Model

A Heterogeneous Accelerated Matrix Multiplication: OpenCL + APU + GPU+ Fast Matrix Multiply

Matrix Multiplication with CUDA – A basic introduction to the CUDA programming model

Performance Exploration of Selected Manually and Automatically Parallelized Codes on GPUs

Algorithm Construction for GPGPU

phiGEMM: a CPU-GPU library for porting Quantum ESPRESSO on hybrid systems

Machine Learning for Predictive Auto-Tuning with Boosted Regression Trees

Strassen’s Matrix Multiplication on GPUs

Optimising the DBCSR GPU Implementation

Generating SU(Nc) pure gauge lattice QCD configurations on GPUs with CUDA and OpenMP

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Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

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

DuoReduce: MLIR's benchmark

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