high performance computing on graphics processing units: hgpu.org

hgpu.org » Sparse matrix

Parallel Application Library for Object Recognition

Bor-Yiing Su

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Tags: Algorithms, ATI, ATI Radeon HD 6970, Computer science, Computer vision, nVidia, nVidia GeForce GTX 480, OpenCL, Sparse matrix, Thesis

October 1, 2012 by hgpu

Improved Row-Grouped CSR Format for Storing of Sparse Matrices on GPU

Tomas Oberhuber, Martin Heller

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Tags: Computer science, CUDA, nVidia, Optimization, Sparse matrix, Tesla C2070

September 26, 2012 by hgpu

Accelerating Iterative SpMV for Discrete Logarithm Problem using GPUs

Hamza Jeljeli

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Tags: Algorithms, Computer science, CUDA, Modular arithmetic, nVidia, nVidia GeForce GTX 580, Security, Sparse matrix

September 26, 2012 by hgpu

SpMV: A Memory-Bound Application on the GPU Stuck Between a Rock and a Hard Place

John D. Davis, Eric S. Chung

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, Sparse matrix

September 22, 2012 by hgpu

Accelerating Sparse Matrix Kernels on Graphics Processing Units

Kiran Kumar Matam

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, Sparse matrix, Tesla C1060, Tesla C2050, Thesis

September 14, 2012 by hgpu

Multi-GPU Implementation of the Uniformization Method for Solving Markov Models

Marek Karwacki, Beata Bylina, Jaroslaw Bylina

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Tags: Computer science, CUDA, nVidia, Sparse matrix, Tesla M2050

August 31, 2012 by hgpu

Large Scale Finite Element Analysis Using GPU Parallel Computing

Ashkan Akbariyeh

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Tags: Algorithms, Computer science, CUDA, Finite element method, nVidia, nVidia Quadro FX 5000, Sparse matrix, Thesis

August 8, 2012 by hgpu

Improving GPU Sparse Matrix-Vector Multiplication for Probabilistic Model Checking

Anton J. Wijs, Dragan Bosnacki

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Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Probabilistic model checking, Sparse matrix

August 6, 2012 by hgpu

Analysis and performance estimation of the conjugate gradient method on multiple GPUs

Mickeal Verschoor, Andrei C. Jalba

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Tags: Computer science, Conjugate gradient solver, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 570, Performance, Sparse matrix

August 4, 2012 by hgpu

New Sparse Matrix Storage Format to Improve The Performance of Total SPMV Time

Neelima Reddy, Raghavendra Prakash, Ram Mohana Reddy

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 470, Sparse matrix

August 1, 2012 by hgpu

Sparse Matrix-Vector Multiplication on NVIDIA GPU

Hui Liu, Song Yu, Zhangxin Chen, Ben Hsieh, Lei Shao

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Tags: Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050, Tesla C2070

July 16, 2012 by hgpu

Sparse Matrix Matrix Multiplication on Hybrid CPU+GPU Platforms

Kiran Kumar Matam, Siva Rama Krishna Bharadwaj, Kishore Kothapalli

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, Optimization, Sparse matrix, Tesla C2050

July 16, 2012 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

Parallel Application Library for Object Recognition

Improved Row-Grouped CSR Format for Storing of Sparse Matrices on GPU

Accelerating Iterative SpMV for Discrete Logarithm Problem using GPUs

SpMV: A Memory-Bound Application on the GPU Stuck Between a Rock and a Hard Place

Accelerating Sparse Matrix Kernels on Graphics Processing Units

Multi-GPU Implementation of the Uniformization Method for Solving Markov Models

Large Scale Finite Element Analysis Using GPU Parallel Computing

Improving GPU Sparse Matrix-Vector Multiplication for Probabilistic Model Checking

Analysis and performance estimation of the conjugate gradient method on multiple GPUs

New Sparse Matrix Storage Format to Improve The Performance of Total SPMV Time

Sparse Matrix-Vector Multiplication on NVIDIA GPU

Sparse Matrix Matrix Multiplication on Hybrid CPU+GPU Platforms

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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