Lecture21 - IE 495 Lecture 21 November 14, 2000 Reading for...

Info iconThis preview shows pages 1–6. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: IE 495 Lecture 21 November 14, 2000 Reading for This Lecture Primary ¡ Miller and Boxer, Pages 124-128 ¡ Forsythe and Mohler, Sections 1 to 8 Matrix Multiplication The standard sequential algorithm for multiplying matrices is O(n 3 ) . Strassen's Algorithm is a divide and conquer approach. Analysis of Strassen's Algorithm ¡ T( n ) = 7T( n /2) + dn 2 ¡ T( n ) = O( n log(7) ) = O( n 2.81... ) Every algorithm must be Ω ( n 2 ) . The best known algorithm to date is O( n 2.376... ) . Can we parallelize Strassen's Algorithm? Parallel Matrix Multiplication Assume a CREW shared-memory architecture with n 3 processors. Label processors as P 111 through P nnn . Processor P ijk calculates a ik ⋅ b kj . The remaining sums can be computed in O(log n) using a semigroup operation. The running time is O(log n) . Cost optimality? Matrix Multiplication on a Mesh Assume a 2n × 2n mesh computer....
View Full Document

This note was uploaded on 08/06/2008 for the course IE 495 taught by Professor Linderoth during the Fall '08 term at Lehigh University .

Page1 / 12

Lecture21 - IE 495 Lecture 21 November 14, 2000 Reading for...

This preview shows document pages 1 - 6. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online