Spring 10-Lec1 - Parallel Processing Several processing...

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Parallel Processing • Several processing elements working to solve a single problem • Primary consideration: elapsed time NOT: throughput, sharing resources, etc. • Downside: complexity – system, algorithm design
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Given a sequence (array) A of n elements (unsorted) find the largest element of A (1), A (2), . .., A ( n ) Serial Algorithm max A (1) for i 2 to n do if A ( i ) > max then max A ( i ) Require n – 1 comparisons: Other associative Optimal? binary functions
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1 2 4 2 1 6 1 4 7 2 5 8 6 9 1 Find the smallest element # Processors, p = 7 = ( n – 1) Input size, n = 8 Parallel time t p = cost = t p p = O ( n log n )   n 2 log For other associative binary ops, max ( a , b ), min ( a , b ) add ( a , b ), multiply ( a , b ) AND, OR
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C C P M M R A L A B B D C A A C K P X U M T R L Q A N B E Y D Input size, n = 16 # processors, p = n / 2 = 8 time, T p = = 4 cost, p T p = ( n / 2)log n = 32   n 2 log
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Prob: Find the largest element in a given set of n elements
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This note was uploaded on 05/12/2010 for the course CS CDA 5110- taught by Professor Deo during the Spring '10 term at University of Central Florida.

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Spring 10-Lec1 - Parallel Processing Several processing...

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