.. backend-support/index.rst Transformer, CPU, GPU, PlaidML ############################### * :ref:`hybrid_transformer` * :ref:`cpu_backend` * :ref:`plaidml_backend` * :ref:`gpu_backend` What is a backend? ------------------ Backends are responsible for function execution and value allocation. They can be used to :doc:`carry out a programmed computation<../howto/execute>` 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 :ref:`plaidml_backend`. .. _hybrid_transformer: Hybrid Transformer ================== Lorem ipsum .. _cpu_backend: CPU Backend =========== Lorem ipsum .. _gpu_backend: GPU Backend =========== Lorem ipsum .. _plaidml_backend: PlaidML Backend =============== The nGraph ecosystem has recently added initial (experimental) support for `PlaidML`_, which is an advanced :abbr:`Machine Learning (ML)` library that can further accelerate training models built on GPUs. When you select the ``PlaidML`` option as a backend, it behaves as an advanced tensor compiler that can further speed up training with large data sets. .. _PlaidML: https://github.com/plaidml