BIT WIDTH SELECTION FOR FIXED POINT NEURAL NETWORKS

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...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: JULIAN, David Jonathan, WIERZYNSKI, Casimir Matthew, ANNAPUREDDY, Venkata Sreekanta Reddy, LIN, Dexu
Format: Patent
Sprache:eng ; fre ; ger
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Beschreibung
Zusammenfassung: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.