I am a beginner in GPU programming and AI. For a project part, I need to train a neural network with NVIDIA Jetson TX2 board. I know there’s plenty of documentation about it but I am running out of time, could someone help me about the following questions ?
The neural network is quite simple :
- 6 numerical inputs (simply numbers).
- A large number of possible numerical outputs (let’s say 1000).
- 1 or 2 hidden layers of approximately 100 neurons each.
- I have to try the following types of neurons : Perceptron, linear, sigmoid, hyperbolic tangent.
I have the data to train the NN: correct output for given inputs
My questions :
What tools should I use to implement that NN as fast as possible ? I think CUDA is used for such implementation but both cuDNN and cuBLAS seem to simplify the task, true ? A template/sample of code implementing a NN similar to the one described above would be perfect !
How to train this implemented NN on the Jetson TX2 ? (connect board and host computer->tools, specific documentation?)
I read the Two Days Demo, but couldn’t understand how to apply it to my own problem, since it is not as complex as Image recognition, segmentation, …
I am sorry, I am asking a lot of simple things and I am sure I would find the solution with a better research but I dont have much time.
Thank you !