Filter löschen
Filter löschen

Using parfor

4 Ansichten (letzte 30 Tage)
Peter
Peter am 27 Apr. 2012
Hi I successfully implemented a parfor loop in Matlab. However on my computer which has 4 cores I am not getting the improvement in computation time I expected to get. When I go to the task manager and check the CPU usage it rarely goes over 25% which is the same as before the parfor loop What could be the problem?

Akzeptierte Antwort

Thomas
Thomas am 27 Apr. 2012
What kind of problem have you set up using parfor.. a general fact about the Parallel Computing Toolbox is that the parallel tasks have to be pretty intensive/expensive in order for parallelization be effective..
If your computation is trivial then you might not get the speedup you expect.. Not a lot more can be said without looking at what code you have parallelized.
Also, is your machine quad core or a two core hyperthreaded which would show up as 4 virtual cores?
  1 Kommentar
Peter
Peter am 27 Apr. 2012
Hi thanks for your reply,
My processor is an Intel(R) Core(TM)2 Quad CPU Q8200 @2.33GHz.
Yes the tasks are pretty heavy.I use bintprog with a hundreds or thousands of variables that take a while to compute and other computationally expensive stuff.
I define the parfor this way on MATLAB 7.5.0(R2007b):
parfor (r=1:m_dash,4)
... end
Is that the correct way?

Melden Sie sich an, um zu kommentieren.

Weitere Antworten (1)

Edric Ellis
Edric Ellis am 2 Mai 2012
One thing to check - have you opened MATLABPOOL before issuing PARFOR? You need to do this in each MATLAB session to make the extra workers available. I.e.
matlabpool open local 4

Kategorien

Mehr zu Parallel for-Loops (parfor) finden Sie in Help Center und File Exchange

Community Treasure Hunt

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

Start Hunting!

Translated by