END-TO-END DATA FORMAT SELECTION FOR HARDWARE IMPLEMENTATION OF DEEP NEURAL NETWORK
Methods for selecting fixed point number formats for representing values input to and/or output from layers of a Deep Neural Network (DNN) which take into account the impact of the fixed point number formats for a particular layer in the DNN. The fixed point number format(s) used to represent sets o...
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Patent |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Methods for selecting fixed point number formats for representing values input to and/or output from layers of a Deep Neural Network (DNN) which take into account the impact of the fixed point number formats for a particular layer in the DNN. The fixed point number format(s) used to represent sets of values input to and/or output from a layer are selected one layer at a time in a predetermined sequence wherein any layer is preceded in the sequence by the layer(s) from which it depends. The fixed point number format(s) for each layer is/are selected based on the error in the output of the DNN associated with the fixed point number formats. Once the fixed point number format(s) for a layer has/have been selected any calculation of the error in the output of the DNN for a subsequent layer in the sequence is based on that layer being configured to use the selected fixed point number formats. |
---|