IP Library Granted Patent US 12,456,053
Granted Patent B2
US 12,456,053 · App. 18/759,661 · Granted Oct 28, 2025

Neural core, neural processor, and data processing method thereof

Inventors: Minhoo Kang (Seongnam-si, KR); Wongyu Shin (Seongnam-si, KR)
Assignee: Rebellions Inc.
G06N3/08G06F3/0625G06F3/0659G06F3/0673G06N3/063
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Quick Facts
Patent No.
US 12,456,053
App. No.
18/759,661
Granted
Oct 28, 2025
Kind
B2
Abstract

A neural core, a neural processor, and a data processing method thereof are provided. The neural core includes a processing unit configured to generate output activation by performing calculation of input activation and a weight, a memory load/store unit configured to generate a memory calculation request requesting one-dimensional calculation of summing the output activation and target data, and a memory configured to receive the output activation and the memory calculation request, import the target data from a memory address in response to the memory calculation request, generate output data by performing the one-dimensional calculation of the target data and the output activation, and store the generated output data in the memory address.

Claims (36)

1 . A neural processing device, comprising:

a memory comprising one-dimensional calculation circuitry and a plurality of memory cells; and

a processor operably coupled to the memory,

wherein the processor is configured to cause:

receiving input activation values and weight values for a neural network;

performing a two-dimensional calculation with the input activation values and the weight values to generate a first value for the neural network; and

requesting the memory to perform a one-dimensional calculation with the first value and a second value in a memory cell referenced by a memory address by using the one-dimensional calculation circuitry within the memory to generate a third value for the neural network and to store the third value in the memory cell referenced by the memory address.

2 . The processing device of claim 1 , further comprising:

load-store unit circuitry configured to load and store operations between the memory and the processor,

wherein requesting the memory further comprises:

sending the first value for the neural network to the load-store unit circuitry.

3 . The processing device of claim 2 ,

wherein the load-store unit circuitry is configured to cause:

loading the input activation values and the weight values from the memory to send the input activation values and the weight values to the processor;

in response to receiving the first value, executing an instruction to send a request requesting the memory to perform the one-dimensional calculation with the first value and the second value stored in the memory cell referenced by the memory address indicated by the instruction by using the one-dimensional calculation circuitry within the memory to generate the third value and to store the third value in the memory cell referenced by the memory address indicated by the instruction.

4 . The processing device of claim 3 ,

wherein the memory is configured to cause:

in response to receiving the request, reading the second value stored in the memory cell referenced by the memory address indicated by the request without using the load-store unit circuitry;

performing the one-dimensional calculation with the first value and the second value to generate the third value by using the one-dimensional calculation circuitry within the memory; and

storing the third value in the memory cell referenced by the memory address indicated by the request.

5 . A method performed by a processing device comprising a memory and a processor operably coupled to the memory, wherein the memory comprises one-dimensional calculation circuitry and a plurality of memory cells, the method comprising:

receiving, by the processor, input activation values and weight values for a neural network;

performing, by the processor, a two-dimensional calculation with the input activation values and the weight values to generate a first value for the neural network; and

requesting, by the processor, the memory to perform a one-dimensional calculation with the first value and a second value in a memory cell referenced by a memory address by using the one-dimensional calculation circuitry within the memory to generate a third value for the neural network and to store the third value for the neural network in the memory cell referenced by the memory address.

6 . The method of claim 5 , wherein the processing device further comprises load-store unit circuitry configured to load and store operations between the memory and the processor, the method further comprising:

sending, by the processor, the first value for the neural network to the load-store unit circuitry.

7 . The method of claim 6 , further comprising:

loading, by the load-store unit circuitry, the input activation values and the weight values from the memory to send the input activation values and the weight values to the processor; and

in response to receiving the first value, executing, by the load-store unit circuitry, an instruction to send a request requesting the memory to perform the one-dimensional calculation with the first value and the second value stored in the memory cell referenced by the memory address indicated by the instruction by using the one-dimensional calculation circuitry within the memory to generate the third value and to store the third value in the memory cell referenced by the memory address indicated by the instruction.

8 . The method of claim 7 , further comprising

in response to receiving the request, reading, by the one-dimensional calculation circuitry within the memory, the second value stored in the memory cell referenced by the memory address indicated by the request without using the load-store unit circuitry;

performing, by the one-dimensional calculation circuitry within the memory, the one-dimensional calculation with the first value and the second value to generate the third value; and

storing the third value in the memory cell referenced by the memory address indicated by the request.

9 . The method of claim 8 , wherein the one-dimensional calculation circuitry is associated with a set of memory cells belonging to a bank in the memory.

10 . The method of claim 9 ,

wherein the second value stored in the memory cell referenced by the memory address is read and the third value is stored via a port which is used by both the one-dimensional calculation circuitry and a controller controlling the bank.

Assignments (1)
MERGER AND CHANGE OF NAME Recorded May 22, 2025
From: REBELLIONS INC.; SAPEON KOREA INC.
To: REBELLIONS INC.
Reel/Frame 071355/0107 →
Priority Claims (1)
KR 10-2022-0185936 · Dec 27, 2022 · national
Continuity (2)
Division 18508156 · Nov 13, 2023
Related Publication 20240354572A1 · Oct 24, 2024
References Cited (11)
US 11537838B2 · Norden et al. · 2022 [cited by applicant]
US 11861401B2 · Yoon · 2024 [cited by applicant]
US 20180121796A1 · Deisher · 2018 [cited by examiner]
US 20210192326A1 · Park · 2021 [cited by applicant]
US 20230214636A1 · Lee · 2023 [cited by applicant]
KR 1020200143479A · 2020 [cited by applicant]
KR 102258566B1 · 2021 [cited by applicant]
KR 1020210081663A · 2021 [cited by applicant]
KR 102480287B1 · 2022 [cited by applicant]
KR 102480300B1 · 2022 [cited by applicant]
Office Action for KR 10-2022-0185936 by Korean Intellectual Property Office dated Sep. 6, 2024. [cited by applicant]