Methods and systems for selecting number formats for deep neural networks based on network sensitivity and quantisation error

A computing-based device for determining a number format for representing a set of two or more network parameters of a Deep Neural Network “DNN” for use in configuring hardware logic to implement the DNN, the computing-based device comprising:

• at least one processor;
• and
• memory coupled to the at least one processor, the memory comprising computer readable code that when executed by the at least one processor causes the at least one processor to:
• determine a sensitivity of the DNN with respect to each network parameter in the set of network parameters;
• for each candidate number format of a plurality of candidate number formats:
• determine a quantisation error associated with quantising each network parameter in the set of network parameters in accordance with the candidate number format,
• generate an estimate of an error in an output of the DNN caused by quantisation of the set of network parameters based on the sensitivities and the quantisation errors, and
• generate a local error based on the estimated error;
• and
• select the candidate number format with the minimum local error as the number format for the set of network parameters.