high performance computing on graphics processing units: hgpu.org

hgpu.org » BLAS

Efficient Support for Matrix Computations on Heterogeneous Multi-core and Multi-GPU Architectures

Fengguang Song, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, BLAS, Computer science, CUDA, Factorization, Heterogeneous systems, nVidia, Tesla M2070

November 20, 2011 by hgpu

Auto-tunable GPU BLAS

Jarle Erdal Steinsland

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Tags: Algorithms, ATI, ATI Radeon HD 5750, ATI Radeon HD 5870, BLAS, Computer science, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, OpenCL, Optimization, Tesla C2070, Thesis

November 18, 2011 by hgpu

Solving Linear Recurrences on Hybrid GPU Accelerated Manycore Systems

Przemyslaw Stpiczynski

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Tags: Algorithms, BLAS, Computer science, CUDA, Hybrid computing, Linear Algebra, nVidia, Tesla C2050

October 21, 2011 by hgpu

A framework to implement a multifrontal scheme on GPU architectures with OpenCL

Federico Edoardo Bonelli

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Tags: BLAS, Computer science, Linear Algebra, nVidia, OpenCL, Performance, Thesis

September 27, 2011 by hgpu

Compiling Python to a hybrid execution environment

Rahul Garg, Jose Nelson Amaral

Tags: ATI, ATI CAL, BLAS, Compilers, Computer science, OpenCL, Python

August 21, 2011 by hgpu

High Performance Matrix Inversion on a Multi-core Platform with Several GPUs

Pablo Ezzatti, Enrique S. Quintana-Orti, Alfredo Remon

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Tags: BLAS, Computer science, CUDA, Linear Algebra, Matrix inversion, nVidia, Presentation, Tesla C1060

July 5, 2011 by hgpu

Accelerating GPU kernels for dense linear algebra

Rajib Nath, Stanimire Tomov, Jack Dongarra

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

June 4, 2011 by hgpu

Mixed-Tool Performance Analysis on Hybrid Multicore Architectures

Peng Du, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Performance

June 3, 2011 by hgpu

Application of the OpenCL API for Implementation of the NIPALS Algorithm for Principal Component Analysis of Large Data Sets

Joshua C. Bowden

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Tags: BLAS, Computer science, GPU cluster, MPI, nVidia, nVidia Quadro FX 580, OpenCL, Performance, Tesla C1060, Tesla S2050, Tesla T10

March 31, 2011 by hgpu

Acceleration of Hessenberg Reduction for Nonsymmetric Eigenvalue Problems Using GPU

Jun-ichi Muramatsu, Shao-Liang Zhang, Yusaku Yamamoto

Tags: BLAS, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C1060

March 28, 2011 by hgpu

GEMM on a GPU

Jonathan Monette

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia Quadro FX 5800, Poster

March 12, 2011 by hgpu

An Improved Magma Gemm For Fermi Graphics Processing Units

Rajib Nath, Stanimire Tomov, Jack Dongarra

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Source codes

Tags: BLAS, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Package, Tesla C2050

January 23, 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

Efficient Support for Matrix Computations on Heterogeneous Multi-core and Multi-GPU Architectures

Auto-tunable GPU BLAS

Solving Linear Recurrences on Hybrid GPU Accelerated Manycore Systems

A framework to implement a multifrontal scheme on GPU architectures with OpenCL

Compiling Python to a hybrid execution environment

High Performance Matrix Inversion on a Multi-core Platform with Several GPUs

Accelerating GPU kernels for dense linear algebra

Mixed-Tool Performance Analysis on Hybrid Multicore Architectures

Application of the OpenCL API for Implementation of the NIPALS Algorithm for Principal Component Analysis of Large Data Sets

Acceleration of Hessenberg Reduction for Nonsymmetric Eigenvalue Problems Using GPU

GEMM on a GPU

An Improved Magma Gemm For Fermi Graphics Processing Units

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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