IP Library › Granted Patent US 11,733,968
Granted Patent B2
US 11,733,968 · App. 16/439,928 · Granted Aug 22, 2023

Neural processing unit, neural processing system, and application system

Inventors: Young Nam Hwang (Hwaseong-si, KR); Hyung-Dal Kwon (Hwaseong-si, KR); Dae Hyun Kim (Suwon-si, KR)
Assignee: SAMSUNG ELECTRONICS CO., LTD.
G06F7/5443G06F17/15G06N3/045G06N3/063
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,733,968
App. No.
16/439,928
Granted
Aug 22, 2023
Kind
B2
Abstract

Provided is a neural processing unit that performs application-work including a first neural network operation, the neural processing unit includes a first processing core configured to execute the first neural network operation, a hardware block reconfigurable as a hardware core configured to perform hardware block-work, and at least one processor configured to execute computer-readable instructions to distribute a part of the application-work as the hardware block-work to the hardware block based on a first workload of the first processing core.

Claims (25)

1. A neural processing unit configured to perform application-work including a first neural network operation, the neural processing unit comprising:

a first processing core configured to execute the first neural network operation;

a hardware block reconfigurable as a hardware core configured to perform hardware block-work, the hardware block being reconfigurable between different types of hardware cores for performing different types of operations, and the different types of operations including different types of neural network operations; and

at least one processor configured to execute computer-readable instructions to

distribute a part of the application-work as the hardware block-work to the hardware block based on a first workload of the first processing core, and

reconfigure the hardware block as a first type of hardware core for performing a first type of operation included in the hardware block-work, the first type of hardware core being among the different types of hardware cores, the first type of operation being among the different types of operations, and the first neural network operation including the first type of operation.

2. The neural processing unit of claim 1 , wherein the at least one processor is configured to execute computer-readable instructions to distribute a part of the first neural network operation as the hardware block-work to the hardware block depending on whether the first workload exceeds a defined value.

3. The neural processing unit of claim 1 , wherein the at least one processor is configured to execute computer-readable instructions to reconfigure the hardware block as a convolutional neural network (CNN) processing hardware core when the hardware block-work includes a CNN operation.

4. The neural processing unit of claim 3 , wherein the CNN operation comprises image recognition processing.

5. The neural processing unit of claim 1 , wherein the at least one processor is configured to execute computer-readable instructions to reconfigure the hardware block as a recurrent neural network (RNN) processing hardware core when the hardware block-work includes an RNN operation.

6. The neural processing unit of claim 5 , wherein the RNN operation comprises voice recognition processing.

7. The neural processing unit of claim 1 , wherein

the first neural network operation comprises a first multiply and accumulate (MAC) operation, and

the at least one processor is configured to execute computer-readable instructions to distribute a part of the first MAC operation as the hardware block-work to the hardware block based on a ratio of the first MAC operation and the first workload.

8. The neural processing unit of claim 1 , wherein

the at least one processor is configured to execute computer-readable instructions to reconfigure the hardware block as a MAC processing hardware core when the hardware block-work includes a MAC operation, and

the hardware block reconfigured as a MAC processing hardware core is configured to perform the MAC operation using a look-up table including quantized weighted data.

9. The neural processing unit of claim 8 , wherein the look-up table comprises one or more result value obtained based on operating input data and the quantized weighted data.

10. The neural processing unit of claim 1 , further comprising:

a second processing core configured to execute a second neural network operation different from the first neural network operation, wherein

the application-work comprises the second neural network operation, and

at least one processor is configured to execute computer-readable instructions to distribute a part of the first neural network operation or a part of the second neural network operation as the hardware block-work to the hardware block based on the first workload and a second workload of the second processing core.

11. The neural processing unit of claim 10 , wherein the at least one processor is configured to execute computer-readable instructions to

distribute the part of the first neural network operation as the hardware block-work to the hardware block in response to an amount of the first workload being larger than an amount of the second workload, and

distribute the part of the second neural network operation as the hardware block-work to the hardware block in response to the amount of the first workload being smaller than the amount of the second workload.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 19, 2019
From: HWANG, YOUNG NAM; KWON, HYUNG-DAL; KIM, DAE HYUN
To: SAMSUNG ELECTRONICS CO., LTD.
Reel/Frame 049510/0208 →
Priority Claims (1)
KR 10-2018-0137345 · Nov 9, 2018 · national
Continuity (1)
Related Publication 20200151549A1 · May 14, 2020