high performance computing on graphics processing units: hgpu.org

hgpu.org » Linear Algebra

cuIBM — A GPU-accelerated Immersed Boundary Method

Simon K Layton, Anush Krishnan, Lorena A. Barba

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Tags: CUDA, Fluid dynamics, Linear Algebra, nVidia, Optimization, Tesla C2050

September 19, 2011 by hgpu

Implementing Independent Component Analysis in General-Purpose GPU Architectures

Jacquelyne Forgette, Renata Wachowiak-Smolikova, Mark Wachowiak

Tags: Algorithms, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 260, OpenCL, Signal processing

September 8, 2011 by hgpu

A fast GEMM implementation on the cypress GPU

Naohito Nakasato

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Tags: ATI, ATI CAL, ATI IL, ATI Radeon HD 5870, Computer science, Linear Algebra, Matrix multiplication, Performance

August 22, 2011 by hgpu

Mind the gap!: bridging the dichotomy of design and implementation

Donna Kaminskyj Long, Liam Kiemele, Celina Gibbs, Andrew Brownsword, Yvonne Coady

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Tags: Computer science, Linear Algebra, OpenCL, Performance, Presentation, Programming techniques

August 21, 2011 by hgpu

Matrix Multiplication on GPUs with On-Line Fault Tolerance

Chong Ding, Christer Karlsson, Hui Liu, Teresa Davies, Zizhong Chen

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

August 9, 2011 by hgpu

Using Graphics Processors to Accelerate the Solution of Out-of-Core Linear Systems

Mercedes Marques, Gregorio Quintana-Orti, Enrique S. Quintana-Orti, Robert van de Geijn

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Tags: Computer science, CUBLAS, CUDA, Factorization, Linear Algebra, nVidia, nVidia GeForce 9800 GX2

August 4, 2011 by hgpu

Linpack evaluation on a supercomputer with heterogeneous accelerators

Toshio Endo, Akira Nukada, Satoshi Matsuoka, Naoya Maruyama

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Tags: Benchmarking, Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Performance, Tesla S1070

July 17, 2011 by hgpu

Testing Tesla architecture for scientific computing: The performance of matrix-vector product

Pawel Maciol, Krzysztof Banas

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce 8800 GTX, Performance, Tesla C870

July 10, 2011 by hgpu

Numerical Parallel Processing Based on GPU with CUDA Architecture

Chengming Zou, Chunfen Xia, Guanghui Zhao

Tags: Algorithms, Computer science, CUDA, Linear Algebra, Matrix inversion, nVidia

July 9, 2011 by hgpu

Acceleration of Streamed Tensor Contraction Expressions on GPGPU-Based Clusters

Wenjing Ma, Sriram Krishnamoorthy, Oreste Villa, Karol Kowalski

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Tags: Computational chemistry, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Presentation, Tesla C1070, Tesla S1070

July 7, 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

Implementing Sparse Matrix-Vector multiplication using CUDA based on a hybrid sparse matrix format

Wei Cao, Lu Yao, Zongzhe Li, Yongxian Wang, Zhenghua Wang

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

June 20, 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

cuIBM — A GPU-accelerated Immersed Boundary Method

Implementing Independent Component Analysis in General-Purpose GPU Architectures

A fast GEMM implementation on the cypress GPU

Mind the gap!: bridging the dichotomy of design and implementation

Matrix Multiplication on GPUs with On-Line Fault Tolerance

Using Graphics Processors to Accelerate the Solution of Out-of-Core Linear Systems

Linpack evaluation on a supercomputer with heterogeneous accelerators

Testing Tesla architecture for scientific computing: The performance of matrix-vector product

Numerical Parallel Processing Based on GPU with CUDA Architecture

Acceleration of Streamed Tensor Contraction Expressions on GPGPU-Based Clusters

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

Implementing Sparse Matrix-Vector multiplication using CUDA based on a hybrid sparse matrix format

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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