Parellel computing toolbox speedup

Hello, I've got some computationally intensive problems to solve so i downloaded the parallel computing toolbox but when testing, parfor loops take longer than for loops even in large loops (for loop takes 55secs while parfor takes 60secs). I would think these loops are big enough to overcome the overhead costs of palatalization. I'm running an iMac with an i7 quad core and 32 gb ram. I'm not using a cluster, i'm trying to utilize all of my cores. Is there some sort of configuration I need to change? Might it be intel's hyperthreading causing a problem? Any input would be appriciated

[Sean de Wolski]

How many workers are you opening? Are your variables sliced? How much data is being transferred back and forth relative to computation time? Posting a small snippet of code might help us diagnose this as well.

[Jonathan Sullivan]

perhaps this for loop and be vectorized. The possible time savings through vectorization can be quite significant, depending on the code. If you post your code, maybe we can take a crack at it.

[Walter Roberson]

_Potentially_ related: http://www.mathworks.com/matlabcentral/answers/30073-extremely-slow-script-execution-with-new-laptop

[Sarah Wait Zaranek]

Did you make sure to open up a matlab pool?

[Jan]

4 very good comments. Actually good enough to be votable answers.

Answer 1

[Daniel Shub]

Not all problems can be sped up with parallel processing on a single computer. MATLAB automatically utilizes all cores for a number of its standard functions. If your processing is not processor limited, or if MATLAB is already using all your processing power, the PCT will not help.