US 12,205,630 B2
Symmetric memory cell and BNN circuit
Qing Luo, Beijing (CN); Bing Chen, Beijing (CN); Hangbing Lv, Beijing (CN); Ming Liu, Beijing (CN); and Cheng Lu, Beijing (CN)
Assigned to INSTITUTE OF MICROELECTRONICS, CHINESE ACADEMY OF SCIENCES, Beijing (CN)
Appl. No. 18/005,101
Filed by INSTITUTE OF MICROELECTRONICS, CHINESE ACADEMY OF SCIENCES, Beijing (CN)
PCT Filed Aug. 24, 2020, PCT No. PCT/CN2020/110781
§ 371(c)(1), (2) Date Jan. 11, 2023,
PCT Pub. No. WO2022/040853, PCT Pub. Date Mar. 3, 2022.
Prior Publication US 2023/0267990 A1, Aug. 24, 2023
Int. Cl. G11C 11/4096 (2006.01); G11C 11/408 (2006.01); G11C 11/4094 (2006.01); H03K 19/017 (2006.01)
CPC G11C 11/4096 (2013.01) [G11C 11/4085 (2013.01); G11C 11/4094 (2013.01); H03K 19/01742 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A BNN circuit, comprising a multi-level neural network layer, wherein each level of the neural network layer of the multi-level neural network layer comprises:
a plurality of memory cell array groups arranged in parallel in a second direction;
wherein each memory cell array group among the plurality of memory cell array groups comprises:
a plurality of symmetric memory cells, arranged in a first direction for storing a weight value 1 or 0; and
an interface module arranged at one end of each memory cell array group, and configured for an input and an output of each memory cell array group,
wherein the interface module comprises:
a first inverter;
a second inverter connected to the first inverter in series and configured to correct an output waveform to a high level and/or a low level binarization,
wherein the interface module further comprises:
a third inverter, wherein one end of the third inverter is connected to a working voltage VDD, and another end of the third inverter is connected to a VGND, an input end of the third inverter is connected to an output end of the second inverter, and an output end of the third inverter is connected to a complementary word line of a next level neural network layer adjacent to the each level of the neural network layer.