METHOD FOR CONSTRUCTING PROCESSORS FOR OUTPUT IN CONVOLUTIONAL NEURAL NETWORKS BASED ON DATA-FLOW COMPUTING Russian patent published in 2020 - IPC G06N3/04 G06N5/04 

Abstract RU 2732201 C1

FIELD: physics.

SUBSTANCE: invention relates to a method of constructing neural network processors for output in convolutional neural networks and a neural network processor. Method comprises arranging, on one integrated circuit of a neural network processor, computer elements which are located in nodes of a regular grid, as well as shared register files which contain locally stored data, wherein each shared register file is connected to several neighbouring computing elements, each of which in turn processes data from shared register files, and then storing output data of calculations in said shared register files; wherein on one or more sides of the integrated circuit to a set of extreme shared register files are connected to the same side of input-output controllers.

EFFECT: technical result is faster operation of the convolutional neural networks.

10 cl, 3 dwg, 1 tbl

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RU 2 732 201 C1

Authors

Shadrin Anton Viktorovich

Chuprik Anastasiya Aleksandrovna

Kondratyuk Ekaterina Vladimirovna

Mikheev Vitalij Vitalevich

Kirtaev Roman Vladimirovich

Negrov Dmitrij Vladimirovich

Dates

2020-09-14Published

2020-02-17Filed