Quantization

Quantization is a promising technique to reduce the computation cost of neural network training, which can replace high-cost floating-point numbers (e.g., float32) with low-cost fixed-point numbers (e.g., int8/int16).

<span class="description-source">Source: Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers </span>