Invention Grant
- Patent Title: Multiply-accumulate calculation method and circuit suitable for neural network
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Application No.: US16757421Application Date: 2019-01-24
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Publication No.: US10984313B2Publication Date: 2021-04-20
- Inventor: Bo Liu , Yu Gong , Wei Ge , Jun Yang , Longxing Shi
- Applicant: Southeast University
- Applicant Address: CN Jiangsu
- Assignee: Southeast University
- Current Assignee: Southeast University
- Current Assignee Address: CN Jiangsu
- Agency: JCIPRNET
- Priority: CN201810894109.2 20180808
- International Application: PCT/CN2019/072892 WO 20190124
- International Announcement: WO2020/029551 WO 20200213
- Main IPC: G06N3/063
- IPC: G06N3/063 ; G06F7/50 ; G06F7/523 ; G06F7/544 ; G06N3/08

Abstract:
The present invention relates to the field of analog integrated circuits, and provides a multiply-accumulate calculation method and circuit suitable for a neural network, which realizes large-scale multiply-accumulate calculation of the neural network with low power consumption and high speed. The multiply-accumulate calculation circuit comprises a multiplication calculation circuit array and an accumulation calculation circuit. The multiplication calculation circuit array is composed of M groups of multiplication calculation circuits. Each group of multiplication calculation circuits is composed of one multiplication array unit and eight selection-shift units. The order of the multiplication array unit is quantized in real time by using on-chip training to provide a shared input for the selection-shift units, achieving increased operating rate and reduced power consumption. The accumulation calculation circuit is composed of a delay accumulation circuit, a TDC conversion circuit, and a shift-addition circuit in series. The delay accumulation circuit comprises eight controllable delay chains for dynamically controlling the number of iterations and accumulating data multiple times in a time domain, so as to meet the difference in calculation scale of different network layers, save hardware storage space, reduce calculation complexity, and reduce data scheduling.
Public/Granted literature
- US20200342295A1 MULTIPLY-ACCUMULATE CALCULATION METHOD AND CIRCUIT SUITABLE FOR NEURAL NETWORK Public/Granted day:2020-10-29
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