How to utilize GPU while the classifiers were running on the classification learner application?
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I'm working in Deep Neural Networks in which lot of execution power is needed for computation. I used Tesla K40c and GeForce GTX 1050Ti Parallel Computing Power for features extraction from different pretrained models but at the stage of classification (which is being done by classification learner application) none of the GPU is utilizing. I have configured MATLAB 2018a with CUDA Toolkit 9.2 and cudNN library 9.2. I also tried different versions of MATLAB with different versions of CUDA Toolkit and cudNN library like MATLAB2017a with CUDA Toolkit8.0 and cudNN library version 8.0 and name a few.
My GPU is utilizing while I used matlab function "activation" for extracting features but GPU utilization has ended during the computation of all the classifiers while using classification learner app.
So, I need to utilize my GPU power while using the classification learner app to minimize the execution time during testing.
I have install all the required toolboxes like Neural Network Toolbox, Parallel Computing Toolbox and Pretrained Models.
Need help to solve this query, waiting for your response.
Bernhard Suhm on 24 Sep 2018
This page lists all the functions that support gpuArray, so far just a couple statistical and "classic" machine learning ones. But not all "classic" machine learning algorithms lend themselves to parallelization on a GPU.