BIT WIDTH SELECTION FOR FIXED POINT NEURAL NETWORKS

A method for selecting bit widths for a fixed point machine learning model includes evaluating a sensitivity of model accuracy to bit widths at each computational stage of the model. The method also includes selecting a bit width for parameters, and/or intermediate calculations in the computational...

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Bibliographic Details
Main Authors JULIAN, David Jonathan, WIERZYNSKI, Casimir Matthew, ANNAPUREDDY, Venkata Sreekanta Reddy, LIN, Dexu
Format Patent
LanguageEnglish
French
German
Published 10.03.2021
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:A method for selecting bit widths for a fixed point machine learning model includes evaluating a sensitivity of model accuracy to bit widths at each computational stage of the model. The method also includes selecting a bit width for parameters, and/or intermediate calculations in the computational stages of the mode. The bit width for the parameters and the bit width for the intermediate calculations may be different. The selected bit width may be determined based on the sensitivity evaluation.
Bibliography:Application Number: EP20160718942