QUANTIZATION METHOD FOR PARTIAL SUMS OF CONVOLUTION NEURAL NETWORK BASED ON COMPUTING-IN-MEMORY HARDWARE AND SYSTEM THEREOF

專利類型

發明

專利國別 (專利申請國家)

美國

專利申請案號

16/784,218

專利證號

US 11,423,315

專利獲證名稱

QUANTIZATION METHOD FOR PARTIAL SUMS OF CONVOLUTION NEURAL NETWORK BASED ON COMPUTING-IN-MEMORY HARDWARE AND SYSTEM THEREOF

專利所屬機關 (申請機關)

國立清華大學

獲證日期

2022/08/23

技術說明

A quantization method for a plurality of partial sums of a convolution neural network based on a computing-in-memory hardware includes a probability-based quantizing step and a margin-based quantizing step. The probability-based quantizing step includes a network training step, a quantization-level generating step, a partial-sum quantizing step, a first network retraining step and a first accuracy generating step. The margin-based quantizing step includes a quantization edge changing step, a second network retraining step and a second accuracy generating step. The quantization edge changing step includes changing a quantization edge of at least one of a plurality of quantization levels. The probability-based quantizing step is performed to generate a first accuracy value, and the margin-based quantizing step is performed to generate a second accuracy value. The second accuracy value is greater than the first accuracy value.

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