Minimizing Communication in Numerical Linear Algebra

In 1981 Hong and Kung proved a lower bound on the amount of communication (amount of data moved between a small, fast memory and large, slow memory) needed to perform dense, n-by-n matrix multiplication using the conventional O(n3) algorithm, where the input matrices were too large to fit in the sma...

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Vydáno v:	SIAM journal on matrix analysis and applications Ročník 32; číslo 3; s. 866 - 901
Hlavní autoři:	Ballard, Grey, Demmel, James, Holtz, Olga, Schwartz, Oded
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Philadelphia, PA Society for Industrial and Applied Mathematics 01.07.2011
Témata:	Algebra Algorithms Applied mathematics Bandwidths Bottlenecks Combinatorics Combinatorics. Ordered structures Communication Computer science Costs Eigenvalues Exact sciences and technology Graph theory Linear algebra Linear and multilinear algebra, matrix theory Mathematics Nonlinear algebraic and transcendental equations Numerical analysis Numerical analysis. Scientific computation Numerical linear algebra Sciences and techniques of general use Composition algebra 68Q25 Costs Multiplication 68W40 Processor Memory Singular value G8W10 Bandwith selection latency Eigenvalue communication-avoiding Parallel 65Y10 Computing Direct method linear algebra algorithms Input G5F30 Cholesky method Bandwidth Communication Dense matrix Lower bound Parallel algorithm LU factorization Optimal algorithm Numerical linear algebra 65Y20 68W15 65Y05 Numerical analysis Graph Experimental design Linear algebra QR factorization Arithmetic operation Variety Power
ISSN:	0895-4798, 1095-7162
On-line přístup:	Získat plný text
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