What is a backend?¶
Backends are responsible for function execution and value allocation. They can be used to carry out a programmed computation from a framework by using a CPU or GPU; or they can be used with an Interpreter mode, which is primarily intended for testing, to analyze a program, or for a framework developer to develop customizations. Experimental APIs to support current and future nGraph Backends are also available; see, for example, the section on PlaidML Backend.
The nGraph ecosystem has recently added initial (experimental) support for PlaidML,
which is an advanced Machine Learning library that can further
accelerate training models built on GPUs. When you select the
as a backend, it behaves as an advanced tensor compiler that can further speed up
training with large data sets.