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www.paperspace.com/ml gets you the cuda power you need. And via ssh it's like on your machine.
good luck 👍 -
@heyheni I could use that. At the cost of losing learning about everything from nothing. What I want to eventually use it for will not tolerate that kind of latency anyway. Thanks tho.
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The week before project deadline...
I'm reinventing the wheel by making yet another neural network library. It's not any good yet but I learn as I go along.
The only documentation that exists now is the admittedly quite comprehensive code comments. I'm it because Keras (using TensorFlow) requires a 3.5 compute ability rating for CUDA acceleration (which I don't have) and it doesn't support OpenCL. Eventually, I will make my implementation support both with varying levels of acceleration for different compute capabilities with the oldest supported being my hardware. If I ever get around to it.
I'd say wish me luck but determination would be infinitely more useful.
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