Deep Learning with TensorFlow - Second Edition
by Giancarlo Zaccone, Vihan Jain, Md. Rezaul Karim, Motaz Saad
Summary
In this chapter, we had a quick look at two fundamentals topics related to optimizing the computation of DNNs.
The first topic explained how to use GPUs and TensorFlow to implement DNNs. They are structured in a very uniform manner so that, at each layer of the network, thousands of identical artificial neurons perform the same computation. Hence, the architecture of a DNN fits quite well with the kinds of computation that a GPU can efficiently perform.
The second topic introduced distributed computing. This was initially used to perform very complex calculations that could not be completed by a single machine. Likewise, analyzing large amounts of data quickly by splitting this task among different nodes appears to be the best strategy when ...
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