<--- Back to Details
First PageDocument Content
Parallel computing / GPGPU / Numerical linear algebra / Computational science / Programming paradigms / OpenCL / General-purpose computing on graphics processing units / Basic Linear Algebra Subprograms / Automatic vectorization / Compute kernel / Kernel / Matrix multiplication algorithm
Date: 2016-01-27 04:16:13
Parallel computing
GPGPU
Numerical linear algebra
Computational science
Programming paradigms
OpenCL
General-purpose computing on graphics processing units
Basic Linear Algebra Subprograms
Automatic vectorization
Compute kernel
Kernel
Matrix multiplication algorithm

Writing a performance-portable matrix multiplication

Add to Reading List

Source URL: www.des.udc.es

Download Document from Source Website

File Size: 445,49 KB

Share Document on Facebook

Similar Documents

13 Numerical Linear Algebra We consider here the numerical side of linear algebra, the symbolic side being described in Chapter 8. The linear algebra numerical analysis and methods are discussed in [TBI97, Sch02]. The b

DocID: 1tLKo - View Document

NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS Numer. Linear Algebra Appl. 2001; 00:1–6 Prepared using nlaauth.cls [Version: v1.0] Preconditioning KKT systems

DocID: 1t9SY - View Document

Assignment 3 Randomization in Numerical Linear Algebra (PCMI) 1. Let A be an n × d matrix with n  d. (i) Give an example of a matrix A whose row leverage scores are all equal. (ii) Give an example of a matrix A whose r

DocID: 1sv5W - View Document

Software / Mathematical software / Application software / Numerical software / Numerical linear algebra / Array programming languages / Econometrics software / ScaLAPACK / PBLAS / LAPACK / Basic Linear Algebra Subprograms / MATLAB

Microsoft PowerPoint - lacsi-sans-1006

DocID: 1ru2M - View Document

Algebra / Mathematics / Mathematical analysis / Fourier analysis / Linear algebra / Binary operations / Basis function / Numerical analysis / Numerical linear algebra / Exponentiation

Time Series Lesson 9 Grant Foster Representing Data

DocID: 1rs99 - View Document