<--- Back to Details
First PageDocument Content
Algebra / Linear algebra / Mathematics / Numerical linear algebra / Basic Linear Algebra Subprograms / General-purpose computing on graphics processing units / Cholesky decomposition / LAPACK / Matrix / Fermi / LU decomposition / Compute kernel
Date: 2016-04-12 16:18:01
Algebra
Linear algebra
Mathematics
Numerical linear algebra
Basic Linear Algebra Subprograms
General-purpose computing on graphics processing units
Cholesky decomposition
LAPACK
Matrix
Fermi
LU decomposition
Compute kernel

On the Development of Variable Size Batched Computation for Heterogeneous Parallel Architectures Ahmad Abdelfattah∗ , Azzam Haidar∗ , Stanimire Tomov∗ , Jack Dongarra∗†‡ {ahmad,haidar,tomov,dongarra}@icl.utk.

Add to Reading List

Source URL: icl.cs.utk.edu

Download Document from Source Website

File Size: 708,62 KB

Share Document on Facebook

Similar Documents

2  C++ API for BLAS and LAPACK Mark Gates Piotr Luszczek Ahmad Abdelfattah

2 C++ API for BLAS and LAPACK Mark Gates Piotr Luszczek Ahmad Abdelfattah

DocID: 1xVIh - View Document

How LAPACK library enables Microsoft Visual Studio support with CMake and LAPACKE Julie Langou1, Bill Hoffman2, Brad King2 1.  University of Tennessee Knoxville, USA

How LAPACK library enables Microsoft Visual Studio support with CMake and LAPACKE Julie Langou1, Bill Hoffman2, Brad King2 1. University of Tennessee Knoxville, USA

DocID: 1udh7 - View Document

Microsoft PowerPoint - lacsi-sans-1006

Microsoft PowerPoint - lacsi-sans-1006

DocID: 1ru2M - View Document

MAGMA (Matrix Algebra on GPU and Multicore Architectures) is a collection of next generation linear algebra libraries for heterogeneous architectures. MAGMA is designed and implemented by the team that developed LAPACK a

MAGMA (Matrix Algebra on GPU and Multicore Architectures) is a collection of next generation linear algebra libraries for heterogeneous architectures. MAGMA is designed and implemented by the team that developed LAPACK a

DocID: 1r9v4 - View Document

Dynamically scheduled Cholesky factorization on multicore architectures with GPU accelerators. Emmanuel Agullo, C´edric Augonnet, Jack Dongarra, Hatem Ltaief, Raymond Namyst, Jean Roman, Samuel Thibault, Stanimire Tomov

Dynamically scheduled Cholesky factorization on multicore architectures with GPU accelerators. Emmanuel Agullo, C´edric Augonnet, Jack Dongarra, Hatem Ltaief, Raymond Namyst, Jean Roman, Samuel Thibault, Stanimire Tomov

DocID: 1qb5g - View Document