Mac Pro configuration for numerical computing with Matlab

At the moment MatLab only supports CUDA for speeding up computations.

http://www.mathworks.com/products/matlab/choosing_hardware.html#_Graphics_Processing_Unit_1

So that means it's an nVidia card and an older Mac Pro if you want GPU acceleration. It's very unlikely, though technically not impossible, to see nVidia cards eventually show up on the new Mac Pro.

http://9to5mac.com/2013/10/25/graphics-card-on-new-mac-pro-could-be-upgradeable/

If you want a real speedup move away from Matlab all together.

Since MC algorithms are embarrassingly parallel you can get linear or even possibly superlinear speedup if you know what you are doing. So assuming you are that good at your implementation, speedup will be on the order of clock*cores, meaning you should have as many cores as possible.

Now, onto the grittier details... you need to efficiently and effectively generate random numbers across as many cores as possible, this is where you are going to see the penalty, unless you use a very good RNG library. I strongly recommend using SPRNG (http://www.sprng.org/) if you want to see that linear speedup.

But this brings me back to my original point... if you want to use a good parallel random number generation library AND see good speedups, you'll have to move away from matlab, regardless of whether you buy a mac pro or not.

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topic 2: GPU

MC algorithms are amazing on the mac pro GPU. I actually just wrote one for pricing american options using PyOpenCL, speedup was ~50x over using 8 cores on the d500s. But once again, Matlab uses CUDA not OpenCL, so you'll need to switch programming languages.

My serious recommendation, look into Python with Numpy. It can do array like expressions similar to matlab, it is faster, and it is more extensible. You can also use the PyOpenCL package for writing code that will execute on the GPUs (http://mathema.tician.de/software/pyopencl).