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US Patent 11954580 Spatial tiling of compute arrays with shared control

Patent 11954580 was granted and assigned to Meta Platforms, Inc. on April, 2024 by the United States Patent and Trademark Office.

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Contents

Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Patent Applicant
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Meta Platforms, Inc.
1
Current Assignee
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Meta Platforms, Inc.
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
119545801
Patent Inventor Names
Harshit Khaitan1
Ganesh Venkatesh1
Vikas Chandra1
Date of Patent
April 9, 2024
1
Patent Application Number
170229501
Date Filed
September 16, 2020
1
Patent Citations
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US Patent 10802956 Accessing prologue and epilogue data
1
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US Patent 11586907 Arithmetic unit for deep learning acceleration
1
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US Patent 11422801 Neural network compute tile
1
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US Patent 9710265 Neural network compute tile
1
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US Patent 9836691 Neural network instruction set architecture
1
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US Patent 10175980 Neural network compute tile
1
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US Patent 10496326 Hardware double buffering using a special purpose computational unit
1
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US Patent 10534607 Accessing data in multi-dimensional tensors using adders
1
Patent Primary Examiner
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Alan Chen
1
CPC Code
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G06F 9/5027
1
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G06N 5/046
1
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G06F 9/3887
1
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G06N 3/063
1
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G06N 3/084
1
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G06F 9/3891
1
Patent abstract

In one embodiment, a method for machine learning acceleration includes receiving, by a shared controller of a tensor processor cluster that includes multiple tensor processors, a multi-cycle instruction, determining, based on the instruction, a sequence of vector operations to be executed by the tensor processors and address information usable to determine a respective spatial partition of an input tensor on which each tensor processor is to operate when performing each vector operation. The method also includes, for each vector operation in the sequence, generating, based on the address information, a common address offset, relative to a respective base address associated with each tensor processor, at which each tensor processor is to retrieve the respective spatial partition on which the tensor processor is to operate, multicasting the common address offset to the tensor processors, and controlling the tensor processors to execute the vector operation in parallel and in lock step.

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