Treffer: Optimization techniques for small matrix multiplication
Title:
Optimization techniques for small matrix multiplication
Authors:
Source:
Theoretical computer science. 412(22):2219-2236
Publisher Information:
Oxford: Elsevier, 2011.
Publication Year:
2011
Physical Description:
print, 40 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Analyse mathématique, Mathematical analysis, Calcul des variations et contrôle optimal, Calculus of variations and optimal control, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Méthodes numériques en programmation mathématique, optimisation et calcul variationnel, Numerical methods in mathematical programming, optimization and calculus of variations, Optimisation et calcul variationnel numériques, Numerical methods in optimization and calculus of variations, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Divers, Miscellaneous, Algorithme, Algorithm, Algoritmo, Anneau polynomial, Polynomial ring, anillo polinómico, Complexité, Complexity, Complejidad, Coût, Costs, Coste, Informatique théorique, Computer theory, Informática teórica, Matrice, Matrices, Méthode optimisation, Optimization method, Método optimización, Nombre entier, Integer, Entero, Optimisation, Optimization, Optimización, Opérateur différentiel, Differential operator, Operador diferencial, Opérateur linéaire, Linear operator, Operador lineal, 34Lxx, 47Axx, 47E05, 47H60, 49XX, 65K10, 65Kxx, 68Wxx, Multiplication matrice, Opérateur récurrence, Matrix multiplication, Small matrix
Document Type:
Fachzeitschrift
Article
File Description:
text
Language:
English
Author Affiliations:
Ancien élève, Ecole polytechnique, Palaiseau, France
Department of Computer Science and ORCCA, The University of Western Ontario, London, ON, Canada
Department of Computer Science and ORCCA, The University of Western Ontario, London, ON, Canada
ISSN:
0304-3975
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Mathematics
Mathematics
Accession Number:
edscal.24076873
Database:
PASCAL Archive
Weitere Informationen
The complexity of matrix multiplication has attracted a lot of attention in the last forty years. In this paper, instead of considering asymptotic aspects of this problem, we are interested in reducing the cost of multiplication for matrices of small size, say up to 30. Following the previous work of Probert & Fischer, Smith, and Mezzarobba, in a similar vein, we base our approach on the previous algorithms for small matrices, due to Strassen, Winograd, Pan, Laderman, and others and show how to exploit these standard algorithms in an improved way. We illustrate the use of our results by generating multiplication codes over various rings, such as integers, polynomials, differential operators and linear recurrence operators.