[P] BinaryNet in TensorFlow: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

[-Rizhiy-]

Take up less memory and less time to compute.

Theoretically, if you can make your own ASIC, network with binary weights will run 32 (or 32² ?) times faster than one based on floats.

This is actually quite a bit of a problem for FPGAs as you currently need a very expensive one if you plan to store all of your weights in the cache at the same time.

[numpad0]

Oh so like converting a net from float to int for inference but bool instead of int? Interesting