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MXNet Architecture

Building a high-performance deep learning library requires many systems-level design decisions. In this design note, we share the rationale for the specific choices made when designing MXNet. We imagine that these insights may be useful to both deep learning practitioners and builders of other deep learning systems.

Deep Learning System Design Concepts

The following pages address general design concepts for deep learning systems. Mainly, they focus on the following 3 areas: abstraction, optimization, and trade-offs between efficiency and flexibility. Additionally, we provide an overview of the complete MXNet system.

.. toctree::
   :maxdepth: 1

   overview.md
   program_model.md
   note_engine.md
   note_memory.md
   note_data_loading.md
   exception_handling.md
   rnn_interface.md

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Sandeep Krishnamurthy, Zack Chase Lipton, Sheng Zha, Aaron Markham, Anirudh Subramanian, Madan Jampani & Yao Wang
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