I am a researcher and I am looking into ways to speed up the Lab data analysys. We use Matlab as a programming language.
Our data analysis consist in taking a movie of ~600 images, we extract some regions of interest (ROIs), ~600xIMAGE, and fit the intensity profiles from those ROIs with a 2D gaussian. The program should be fairly easy to parallelize, since it runs mostly on independent for loops. I know that matlab supports CUDA-enabled NVIDIA GPUs(https://de.mathworks.com/discovery/matlab-gpu.html).
If I use a parfor loop to parallelize my analysis, would my computer use automatically the GPUs?
If not, how can I do it?
Additional questions(maybe not relevant to the topic):
I would like to buy a computer for parallel computing using GPUs, possibly I would like to avoid to build it myself
in spite of an increased price. Unless you highly recommend it.
Some info about the movies. Each movie has about 600 images and each image 600 ROIs to fit with a gaussian, I imagine
that optimally I would need something that can first run the 600 images in parallel to get the ROIs and than the 600 fits.
It should be a computer with GPUs for a total of ~600cores.
Would you suggest any computer?
If you recommend to build it myself, could you elaborate on how to do it?
Budget is not a big issue.
Thank you a lot for your time.
NOTE: JUST KEEP IN MINE THAT MY EXPERTISE ARE VERY LIMITED ABOUT GPUs. I THINK I COULD MOUNT RELATIVELY EASY A HOME-BUILD COMPUTER WITH THE HELP Of GUIDS/YOUTUBE TUTORIALS BUT I WOULD NOT LIKE TO SPEND MORE THAN A FEW DAYS ON IT.