Matrix decomposition

hgpu.org » Matrix decomposition

FC_ACCEL: Enabling Efficient, Low-Latency and Flexible Inference in DNN Fully Connected Layers, using Optimized Checkerboard Block matrix decomposition, fast scheduling, and a resource efficient 1D PE array with a custom HBM2 memory subsystem

Nick Iliev, Amit R Trivedi

View

Tags: CNN, Computer science, Deep learning, FPGA, Matrix decomposition, Neural networks, nVidia, nVidia Jetson AGX Xavier, Performance

February 13, 2022 by hgpu

Using reconfigurable computing technology to accelerate matrix decomposition and applications

Xinying Wang

View

Download (PDF)

Tags: Computer science, Data mining, Factorization, FPGA, Intel Xeon Phi, Matrix decomposition, Semantic indexing, Signal processing, Text mining, Thesis

December 28, 2017 by hgpu

Parallel Implementations of the Cholesky Decomposition on CPUs and GPUs

Joao Paulo Tarasconi Ruschel

View

Download (PDF)

Source codes

Tags: Algorithms, Benchmarking, Computer science, CUDA, Linear Algebra, Matrix decomposition, nVidia, OpenCL, OpenMP, Package, Performance, Tesla K80, Thesis

January 26, 2017 by hgpu

Stability and Performance of Various Singular Value QR Implementations on Multicore CPU with a GPU

Ichitaro Yamazaki, Stanimire Tomov, Jack Dongarra

View

Download (PDF)

Tags: BLAS, Computer science, CUDA, Linear Algebra, Matrix decomposition, Mixed precision, Numerical Analysis, nVidia, Performance, Tesla K20

July 16, 2016 by hgpu

RSVDPACK: Subroutines for computing partial singular value decompositions via randomized sampling on single core, multi core, and GPU architectures

Sergey Voronin, Per-Gunnar Martinsson

View

Download (PDF)

Source codes

Tags: Algorithms, CUDA, CULA, Mathematical Software, Mathematics, Matrix decomposition, Numerical Analysis, nVidia, Package, Tesla M2070

February 22, 2015 by hgpu

Computation on GPU of Eigenvalues and Eigenvectors of a Large Number of Small Hermitian Matrices

Alain Cosnuau

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Linear Algebra, Matrix decomposition, nVidia, Tesla M2070

June 27, 2014 by hgpu

Hybrid algorithms for efficient Cholesky decomposition and matrix inverse using multicore CPUs with GPU accelerators

Gary Macindoe

View

Download (PDF)

Tags: Algorithms, Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, Machine learning, Matrix decomposition, nVidia, nVidia GeForce 9500 GT, nVidia GeForce GTX 285, Tesla S1070, Thesis

January 29, 2014 by hgpu

Tiled QR Decomposition and Its Optimization on CPU and GPU Computing System

Dongjin Kim, Kyu-Ho Park

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Matrix decomposition, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680

November 8, 2013 by hgpu

GPU-Accelerated Scalable Solver for Banded Linear Systems

Hang Liu, Jung-Hee Seo, Rajat Mittal, H. Howie Huang

View

Download (PDF)

Tags: Computer science, CUDA, Diffusion equation, Matrix decomposition, MPI, nVidia, OpenMPI, Poisson equation, Tesla M2050, Tesla M2090

August 16, 2013 by hgpu

Parallel perfusion imaging processing using GPGPU

Fan Zhu, David Rodriguez Gonzalez, Trevor Carpenter, Malcolm Atkinson, Joanna Wardlaw

View

Download (PDF)

Tags: Algorithms, CUDA, Matrix decomposition, Medicine, nVidia, nVidia GeForce GTX 280

August 5, 2012 by hgpu

A GPU-based Approximate SVD Algorithm

Blake Foster, Sridhar Mahadevan, Rui Wang

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Matrix decomposition, nVidia, nVidia GeForce GTX 480, Package

December 15, 2011 by hgpu

Effective GPU Strategies for LU Decomposition

Dinesh Bandara, Nalin Ranasinghe

View

Download (PDF)

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

December 2, 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

* * *

high performance computing on graphics processing units: hgpu.org

FC_ACCEL: Enabling Efficient, Low-Latency and Flexible Inference in DNN Fully Connected Layers, using Optimized Checkerboard Block matrix decomposition, fast scheduling, and a resource efficient 1D PE array with a custom HBM2 memory subsystem

Using reconfigurable computing technology to accelerate matrix decomposition and applications

Parallel Implementations of the Cholesky Decomposition on CPUs and GPUs

Stability and Performance of Various Singular Value QR Implementations on Multicore CPU with a GPU

RSVDPACK: Subroutines for computing partial singular value decompositions via randomized sampling on single core, multi core, and GPU architectures

Computation on GPU of Eigenvalues and Eigenvectors of a Large Number of Small Hermitian Matrices

Hybrid algorithms for efficient Cholesky decomposition and matrix inverse using multicore CPUs with GPU accelerators

Tiled QR Decomposition and Its Optimization on CPU and GPU Computing System

GPU-Accelerated Scalable Solver for Banded Linear Systems

Parallel perfusion imaging processing using GPGPU

A GPU-based Approximate SVD Algorithm

Effective GPU Strategies for LU Decomposition

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

Most viewed papers (last 30 days)