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MATLAB DualCPU Hyper-Threading support

Asked by Emiliano Rosso on 30 Jun 2019
Latest activity Edited by Jan
on 1 Jul 2019
Accepted Answer by Jan
Hello everyone.
I'm going to buy a dual CPU workstation and would like to know if a vectorized MATLAB code uses
all the cores of both CPUs without the need to
use the Parallel Computing Toolbox.


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Thanks,I refer to the use of " : " instead of " for " loop because I have independent process for my matrix. This is a general question not specific for any particular code. So,if I have 2 CPU with 4 (8 thread) cores each I'll use 4 (8) or 8 (16) cores when I use the vectorization function " : " ?
I verified that using 1 intel xeon w3680 6 cores 12 thread I can use all 12 thread even if not 100% powerfull because my RAM is slow. That's the same using 2 cpu (nodes)?
on 30 Jun 2019
I do not understand what
use of " : " instead of " for " loop
means. Of course it depends on the specific code, how it is executed. Calling the colon operator "." a "vectorization function" is strange.
If your code exhausts 12 threads, you can expect that it let 8 threads work efficiently also. So what exactly is your question?
for i=1:m
for l=1:n
I vectorize the code :
if I use 1 cpu xeon w3550 4 cores 8 thread:
1200 sec.
if I use 1 cpu xeon w3680 6 cores 12 thread:
800 sec.
The 2 cpu are identical except for the number of cores and I can verify that all thread are
working in both cases.
Now :
if I use 2 cpu xeon w3680 6 cores 12 thread does my code will use the second cpu?

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1 Answer

Answer by Jan
on 30 Jun 2019
Edited by Jan
on 1 Jul 2019
 Accepted Answer

Yes. Matlab will use the available cores. At least most likely. Matlab might split the array columnwise and if the input has 5 columns, there is a chance that only 5 cores are used. Many functions are multi-threaded, but this is applied for "large" arrays only.
I'm not sure, if hyper-threading is used in Matlab. Maybe only the physical cores are used for the reason of efficiency.
Note that:
for i=1:m
for l=1:n
matrix(i,l) = matrix(i,l)^2;
do not compute the same result. The 2nd code works for square matrices only and is a matrix multiplication. Equivalent to the first code would be:
% No need to determine the size...
matrix(:,:) = matrix(:,:) .^ 2;
% ^ elementwise squaring
It would be even more efficient, to omit the (:,:):
matrix = matrix .^ 2;

  1 Comment

Thanks for your answer.
The " ^ " instead of ".^ " was a mistake.

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