發明
美國
16/902,282
US 11,763,162
DYNAMIC GRADIENT CALIBRATION METHOD FOR COMPUTING-IN-MEMORY NEURAL NETWORK AND SYSTEM THEREOF
國立清華大學
2023/09/19
A dynamic gradient calibration method for a computing-in-memory neural network is performed to update a plurality of weights in a computing-in-memory circuit according to a plurality of inputs corresponding to a correct answer. A forward operating step includes performing a bit wise multiply-accumulate operation on a plurality of divided inputs and a plurality of divided weights to generate a plurality of multiply-accumulate values, and performing a clamping function on the multiply-accumulate values to generate a plurality of clamped multiply-accumulate values according to a predetermined upper bound value, and comparing the clamped multiply-accumulate values with the correct answer to generate a plurality of loss values. A backward operating step includes performing a partial differential operation on the loss values relative to the weights to generate a weight-based gradient. The weights are updated according to the weight-based gradient.
智財技轉組
03-5715131-62219
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