HI, I have an optimization code which has some part code is common and required as inputs for the two optimization routines within. However once this is done, the remaining could be run parallely independednt of each other and imrovized on the speed and finally the two results could be fetched in one single main optimization file and compared. Though i feel this could be done, i do not knopw the exact procedure as well do not know if there is some setting to be done in matlab and modify my main code as well. Please note i have matlab 2007b and distributed computing toolbox v3.2. It would be very kind if somebody could help me with it. Thanks in adavance, Satish

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8/18/2010 9:37:05 AM

Look in the doc for 'Example: Programming a Basic Job with a Local Scheduler'. In step 3, you could create two tasks for the two parallel parts, sending them the same precomputed (from the first step) inputs. If its an option, consider updating the MATLAB version. The newer functions (like BATCH) might be more useful for you.

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8/18/2010 1:49:41 PM

Thanks for the reply. Actually my optimization is related to options and as you say may be i need to update my matlab version. But till i get there is there any way out. Curretly i am not able to parallely compute the two optimization routines in anyways. Now i am confused about DCT and parallel computing toolbox. Though i have DCT v3.2, i do not have parallel computing toolbox. I did read somewhere that the DCT is renamed parallel CT. But does the DCt v3.2 will help me in anyways with the parallel optimization requirement that i have. Please note that i can only run the process on a single core pentium 4 machine. Will my problem be solved or the only way out is to update my matlab which could take some time. thanks Satish

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8/19/2010 8:08:07 AM

I meant option as in 'choice', not as a financial derivative :) Did you get a chance to look at the example I mentioned earlier? You should be able to use that idea to parallelize your code with DCT. (Yes, its been renamed to PCT in later versions). Parallelizing a compute intensive operation (like optimization) would not make much difference if you have a single core machine. If you really need to speed the MATLAB computation, then my first step would be to buy/get access to more powerful compute resources.

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8/19/2010 2:45:14 PM