APPROXIMATING ACTIVATION FUNCTION IN NEURAL NETWORK WITH LOOK-UP TABLE HAVING HYBRID ARCHITECTURE
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United States of America Patent
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Issued Date -
May 16, 2024
app pub date -
Dec 21, 2023
filing date -
Dec 21, 2023
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Abstract
A non-linear activation function may be approximated by linear functions. The input range of the activation function may be divided into input segments. One or more input segments may be selected based on statistical analysis of input data elements in the input range. A parameter of a first linear function that approximates the activation function for at least part of a selected input segment may be stored in a first portion of a first look-up table (LUT). The first portion of the first LUT is dedicated to a first group of post processing engines (PPEs). A parameter of a second linear function that approximates the activation function for at least part of an unselected input segment may be stored in a shared pool of LUT entries, which includes a second portion of the first LUT and a portion of a second LUT and is shared by multiple groups of PPEs.
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