IvyBazan commented on a change in pull request #15137: 1.5.0 news
URL: https://github.com/apache/incubator-mxnet/pull/15137#discussion_r296859958
 
 

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 File path: NEWS.md
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 @@ -17,6 +17,855 @@
 
 MXNet Change Log
 ================
+## 1.5.0
+
+### New Features
+
+#### Automatic Mixed Precision(experimental)
+Training Deep Learning networks is a very computationally intensive task. 
Novel model architectures tend to have increasing number of layers and 
parameters, which slows down training. Fortunately, new generations of training 
hardware as well as software optimizations, make it a feasible task. 
+However, where most of the (both hardware and software) optimization 
opportunities exists is in exploiting lower precision (like FP16) to, for 
example, utilize Tensor Cores available on new Volta and Turing GPUs. While 
training in FP16 showed great success in image classification tasks, other more 
complicated neural networks typically stayed in FP32 due to difficulties in 
applying the FP16 training guidelines.
 
 Review comment:
   Consider changing to: "However, most of the hardware and software 
optimization opportunities exist in exploiting lower precision (e.g. FP16) to, 
for example, utilize Tensor Cores available on new Volta and Turing GPUs.

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