Effective Quantization Approaches for Recurrent Neural Networks

Understand

Deep learning, and in particular Recurrent Neural Networks (RNN) have shown superior accuracy in a large variety of tasks including machine translation, language understanding, and movie frame generation.

• However, these deep learning approaches are very expensive in terms of computation.
• In most cases, Graphic Processing Units (GPUs) are in used for large scale implementations.
• Meanwhile, energy efficient RNN approaches are proposed for deploying solutions on special purpose hardware including Field Programming Gate Arrays (FPGAs) and mobile platforms.