How to optimize the multiplication of large matrices in Matlab?

13 次查看（过去 30 天）
John
John 2013-3-8
评论： Ken 2016-11-18
I have 2 matrices A, B, and vector C that I need to multiply. They are fairly large.
Matrix A = 10000x10000
Matrix B = 10000x10000
Vector C = 10000x1
If I perform A*B*C, this takes a long time so I used sparse function which collapses the matrices/vectors by removing large number of zeros then I convert it back to a full matrix.
full(sparse(A)*sparse(B)*sparse(C))
It's faster but I was wondering if there are more efficient techniques for multiplying them together. Would it be better to write for loops?
Secondly, some of the elements in my matrix have values close to zero so I can replace these with zeroes before converting them to sparse matrices. What's the best way to do this?

请先登录，再回答此问题。

采纳的回答

James Tursa
James Tursa 2013-3-8
Force the matrix-vector multipy to happen first. E.g.,
A*(B*C)

更多回答（2 个）

Sean de Wolski
Sean de Wolski 2013-3-8
I doubt you'll be able to get anything faster than the highly optimized BLAS libraries that MATLAB uses to perform matrix arithmetic. The only thing I've heard of that might be faster is mtimesx on the FEX and even that, I've never reproduced.
per isakson
per isakson 2013-3-8
编辑：per isakson 2013-3-8
Your second question:
A( A < small_number ) = 0;
or better
A( abs(A) < small_number ) = 0;

类别

在 Help Center 和 File Exchange 中查找有关 Sparse Matrices 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by