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there is no reason to train on that thing (except for zero shot classification demos). any cheap/lower end Nvidia gpu would do a much better job, and you would
by make3 8y ago
there is no reason to train on that thing (except for zero shot classification demos). any cheap/lower end Nvidia gpu would do a much better job, and you would then transfer the model to the embedded thing.
- outlace 8y agoWould it do better than a CPU for training? I do my dev on a MacBook Air and use AWS for training, if this cheap gpu will be a few times faster than my Air CPU than I’d be willing to get it. I usually work with medium sized models/data, too big for CPU but don’t need a multi gpu cluster.
- arbie 8y agoI would stick to AWS for training. Your CPU will be orders of magnitude slower than most GPUs for training.
- make3 8y agoGoogle colab gpu instances are free and likely faster than the jetson (and definitely faster then typical laptop or desktop cpu only training), just save the models to your gdrive https://colab.research.google.com/notebooks/welcome.ipynb#recent=true https://colab.research.google.com/notebooks/welcome.ipynb#re...
- anonymousDan 8y agoCan you recommend a cheap/lower end Nvidia GPU for training for someone who just wants to play around with NNs a bit and isn't interested in peak performance? Could I get something for $100 that would be better than my CPU?
- dagw 8y agoWhile you can in theory run CUDA on an Nvidia 1030 GPU (currently around $100) it's really not worth it. The cheapest card actually worth buying for ML is the 1050 Ti, which can be had for around $200. If your budget is $100 I'd take that money and hunt around for various cloud based solutions. Most have introductory offers and/or cheap/free solutions for hobbyists with modest needs. $100 will go a long way on these services if you're careful. Once you've used up your $100 you'll have a much better idea of what, if anything, you actually need.
- make3 8y agothe other options is Google's free gpu instances on it's colab notebooks https://colab.research.google.com/notebooks/welcome.ipynb#recent=true https://colab.research.google.com/notebooks/welcome.ipynb#re... that's what I would recommend for your budget probably
- ashwinne 8y agoThat's correct, you can transfer any trained model to the Nano and run it there using the NVIDIA TensorRT library/toolchain.