Compression

The following tutorials will help you learn how to use compression techniques with MXNet.

Compression: float16https://mxnet.apache.org/api/faq/float16

How to use float16 in your model to boost training speed.

Gradient Compressionhttps://mxnet.apache.org/api/faq/gradient_compression

How to use gradient compression to reduce communication bandwidth and increase speed.

Inference with Quantized Modelshttps://gluon-cv.mxnet.io/build/examples_deployment/int8_inference.html

How to use quantized GluonCV models for inference on Intel Xeon Processors to gain higher performance.

Compression: int8int8.html

How to use int8 in your model to boost training speed.