Memory subsystem in CNN based digital IC for artificial intelligence

US10592804B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10592804-B2
Application numberUS-201916403679-A
CountryUS
Kind codeB2
Filing dateMay 6, 2019
Priority dateApr 3, 2017
Publication dateMar 17, 2020
Grant dateMar 17, 2020

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

CNN based digital IC for AI contains a number of CNN processing units. Each CNN processing unit contains CNN logic circuits operatively coupling to a memory subsystem having first and second memories. The first memory includes an array of magnetic random access memory (RAM) cells for storing weights (e.g., filter coefficients) and the second memory contains SRAM for storing input signals (e.g., imagery data). The first memory may store one-time-programming weights. The memory subsystem may contain a third memory that contains magnetic RAM cells for storing one-time-programming data for security purpose. The magnetic RAM includes STT-RAM or OST-MRAM in SLC or MLC technology.

First claim

Opening claim text (preview).

What is claimed is: 1. A digital integrated circuit for artificial intelligence comprising: a semi-conductor substrate embedded in a single semi-conductor chip, the semi-conductor substrate containing a plurality of cellular neural networks (CNN) processing units, each CNN processing unit comprising: CNN logic circuits; and an embedded memory subsystem operatively coupling to the CNN logic circuits; the embedded memory subsystem further comprising: a first memory containing an array of magnetic random access memory cells configured for storing a set of weights; and a second memory containing an array of static random access memory cells configured for storing the input signals that require higher endurance of balanced data read and write operations than the first memory. 2. The digital integrated circuit of claim 1 , wherein each of the magnetic random access memory cells comprises a single-level cell spin transfer torque magnetic random access memory (SLC STT-RAM) cell. 3. The digital integrated circuit of claim 1 , wherein each of the magnetic random access memory cells comprises a multi-level cell spin transfer torque magnetic random access memory (MLC STT-RAM) cell. 4. The digital integrated circuit of claim 1 , wherein said each of the magnetic random access memory cells comprises a single-level cell orthogonal spin transfer magnetic random access memory (SLC OST-MRAM) cell. 5. The digital integrated circuit of claim 1 , wherein said each of the magnetic random access memory cells comprises a multi-level cell orthogonal spin transfer magnetic random access memory (MLC OST-MRAM) cell. 6. The digital integrated circuit of claim 1 , wherein the semi-conductor substrate comprises a silicon substrate. 7. A digital integrated circuit for artificial intelligence comprising: a semi-conductor substrate embedded in a single semi-conductor chip, containing a plurality of cellular neural networks (CNN) processing units, each CNN processing unit comprising: CNN logic circuits; and an embedded memory subsystem operatively coupling to the CNN logic circuits; the embedded memory subsystem further comprising: a first memory containing an array of magnetic random access memory cells configured for storing a set of one-time-programming weights; and a second memory containing an array of static random access memory cells configured for storing the input signals that require higher endurance of balanced data read and write operations than the first memory. 8. The digital integrated circuit of claim 7 , wherein each of the magnetic random access memory cells comprises a single-level cell spin transfer torque magnetic random access memory (SLC STT-RAM) cell. 9. The digital integrated circuit of claim 7 , wherein each of the magnetic random access memory cells comprises a multi-level cell spin transfer torque magnetic random access memory (MLC STT-RAM) cell. 10. The digital integrated circuit of claim 7 , wherein said each of the magnetic random access memory cells comprises a single-level cell orthogonal spin transfer magnetic random access memory (SLC OST-MRAM) cell. 11. The digital integrated circuit of claim 7 , wherein said each of the magnetic random access memory cells comprises a multi-level cell orthogonal spin transfer magnetic random access memory (MLC OST-MRAM) cell. 12. The digital integrated circuit of claim 7 , wherein each of the magnetic random access memory cells has at least one MTJ element and each MTJ element contains an oxide barrier layer.

Assignees

Inventors

Classifications

  • Hybrid storage combining heterogeneous device types, e.g. hierarchical storage, hybrid arrays · CPC title

  • G06N3/063Primary

    using electronic means · CPC title

  • using field-effect transistors only · CPC title

  • using magnetic storage elements · CPC title

  • in relation to data integrity, e.g. data losses, bit errors · CPC title

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Frequently asked questions

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What does patent US10592804B2 cover?
CNN based digital IC for AI contains a number of CNN processing units. Each CNN processing unit contains CNN logic circuits operatively coupling to a memory subsystem having first and second memories. The first memory includes an array of magnetic random access memory (RAM) cells for storing weights (e.g., filter coefficients) and the second memory contains SRAM for storing input signals (e.g.,…
Who is the assignee on this patent?
Gyrfalcon Tech Inc
What technology area does this patent fall under?
Primary CPC classification G06N3/063. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Mar 17 2020 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 12 related publications on this page (citations in our corpus or others sharing the same primary CPC).