Invention Grant
- Patent Title: Generic quantization of artificial neural networks
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Application No.: US16747103Application Date: 2020-01-20
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Publication No.: US12169769B2Publication Date: 2024-12-17
- Inventor: Benoit Chappet de Vangel , Gabriel Gouvine
- Applicant: Mipsology SAS
- Applicant Address: FR Palaiseau
- Assignee: Mipsology SAS
- Current Assignee: Mipsology SAS
- Current Assignee Address: FR Palaiseau
- Agent Georgiy L. Khayet
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N3/08

Abstract:
Systems and methods for performing a quantization of artificial neural networks (ANNs) are provided. An example method may include receiving a description of an ANN and sets of inputs to neurons of the ANN, the description including sets of weights of the inputs, the weights being of a first data type, determining a first interval of the first data type to be mapped to a second interval of a second data type; performing computations of sums of products of the weights and the inputs to obtain a set of sum results, wherein the computations are performed using at least one number within the second interval, the number being a result of mapping of a number of the first interval to a number of the second interval, determining a measure of saturations in sum results, and adjusting, based on the measure of saturations, one of the first and second intervals.
Public/Granted literature
- US20200242445A1 GENERIC QUANTIZATION OF ARTIFICIAL NEURAL NETWORKS Public/Granted day:2020-07-30
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