- What's your definition of large? How many rows and columns?
- How long is it taking for those large matrices? How many seconds or minutes?
- How much speed do you require? What is the max allowable time?
- Do you have the Parallel Processing Toolbox?
Is there any other function faster than sum(A,2) to get the sum of all rows?
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a=zeros(6750);
h=zeros(6750,1);
tic;k=h-sum(a,2); toc
Is there any faster way than to use sum(A,2) to get the sums of the rows of a matrix? sum(A,2) seems to be slow for large matrices.
4 comentarios
Image Analyst
el 27 de Jun. de 2022
The Parallel Processing Toolbox is an add-on toolbox. You can ask for a free trial of it and see if the Parallel Processing Toolbox helps. I know some functions recognize if you have that toolbox and start parallel processes going on multiple CPU cores on your computer automatically.
Walter Roberson
el 27 de Jun. de 2022
For sufficiently large matrices, addition is automatically handled by high performance parallel libraries. Using parfor or parfeval() will not improve performance compared to the automatic multi-core work that is done.
Respuestas (2)
Walter Roberson
el 26 de Jun. de 2022
Switching to columns can improve performance as it allows better use of hardware cache.
2 comentarios
Walter Roberson
el 27 de Jun. de 2022
When I test on my system, the sum(a,1) version is 5 to 6 times faster than the sum(a,2) version
MJFcoNaN
el 26 de Jun. de 2022
In general, the native functions are optimized sufficiently.
In certain cases, there may be some better way but in other parts of code. For example,
a=sparse(zeros(6750));
h=sparse(zeros(6750,1));
tic;k=h-sum(a,2); toc
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