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title
F# and Data Mining
description
image
site name
author
updated
2026-01-12 11:21:12
raw text
F# and Data Mining F# and Data Mining Monday, January 11, 2016 Improve cache performance: matrix multiplication as an example It is surprising to see mul1() is 10 times slower than mul2(). Mul2: By using j as the inner loop, C[i][j] & B[k][j] have good cache hits, while A[i][k] is a constant during the inner loop. Mul1: In the inner loop, C[i][j] has a constant address, and A[i][k] has good cache hits; however B[k][j] is doomed to cache misses. There are other methods to optimize matrix multiplication, but this one should be the most significant. reference slide: https://www.cs.duke.edu/courses/fall06/cps220/lectures/PPT/lect12.pdf #include #include #include using namespace std; const int N = 2000; double A[N][N], B[N][N], C[N][N]; void fill() { for (int i=0; i
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18 - science.raphael.poss.name, erl.nfshost.com, kyb.mpg.de, petr-mitrichev.blogspot.hk, informatik.uni-ulm.de, cran.r-project.org, fdatamining.blogspot.hk, lh3.ggpht.com, lh4.ggpht.com, lh6.ggpht.com, blogs.msdn.com, cid-701679ad17b6d310.users.api.live.net
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