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Conventional NVIDIA GPUs, such as the Titan and or GT1080, are used to train AI models. Why would a Jetson Nano board be less than ideal as a substitute for a conventional GPU?

CONTEXT

I would like to run simple concept demonstrator training exercises with and without a GPU: that being said, I am not interested in buying a desktop and outfitting it with a $1000+ GPU for said exercise.

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  • $\begingroup$ Answered lol not sure why you edited this $\endgroup$ – hisairnessag3 Apr 5 at 11:01
  • $\begingroup$ Anything else you are looking for out of an answer??? $\endgroup$ – hisairnessag3 Apr 5 at 12:14
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Jetson Nano specs Price:$99:

128-core Maxwell GPU

Quad-core ARM A57 @ 1.43 GHz

472 GFLOPS max compute

Titan V(for example) Price:$2500 :

640 tensor cores

5120 cuda cores

110000 GFLOPS max compute

Some simple maths gets us to a speed of 11,800 GFLOPS for 25 of these perfectly synced in parallel(not likely or gonna be fun). Vs the 110000 it just isn't even a question.

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