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US Patent 11556280 Data transformation for a machine learning model

Patent 11556280 was granted and assigned to Pure Storage on January, 2023 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Pure Storage
Pure Storage
Current Assignee
Pure Storage
Pure Storage
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11556280
Date of Patent
January 17, 2023
Patent Application Number
16888402
Date Filed
May 29, 2020
Patent Citations
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US Patent 10275285 Data transformation caching in an artificial intelligence infrastructure
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US Patent 10157442 System and method for performing queries and displaying visual representations of their results using graphics processing units
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US Patent 10176217 Dynamically performing data processing in a data pipeline system
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US Patent 10275176 Data transformation offloading in an artificial intelligence infrastructure
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US Patent 10649988 Artificial intelligence and machine learning infrastructure
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US Patent 10671434 Storage based artificial intelligence infrastructure
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US Patent 10671435 Data transformation caching in an artificial intelligence infrastructure
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US Patent 10776322 Transformation processing for objects between storage systems
...
Patent Citations Received
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US Patent 12067466 Artificial intelligence and machine learning hyperscale infrastructure
0
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US Patent 11803338 Executing a machine learning model in an artificial intelligence infrastructure
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US Patent 11768636 Generating a transformed dataset for use by a machine learning model in an artificial intelligence infrastructure
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US Patent 11861423 Accelerating artificial intelligence (‘AI’) workflows
0
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US Patent 11824924 Service request message sending method, distributed database architecture and computer readable storage medium
0
Patent Primary Examiner
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Kyung H Shin
CPC Code
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G06F 16/289
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G06Q 30/0243
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G06Q 30/0244
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G06Q 30/0277
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G06Q 30/0271
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G06F 16/1794
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G06F 9/34
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G06F 13/38
...

Data transformation caching in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: identifying, in dependence upon one or more machine learning models to be executed on the GPU servers, one or more transformations to apply to a dataset; generating, in dependence upon the one or more transformations, a transformed dataset; storing, within one or more of the storage systems, the transformed dataset; receiving a plurality of requests to transmit the transformed dataset to one or more of the GPU servers; and responsive to each request, transmitting, from the one or more storage systems to the one or more GPU servers without re-performing the one or more transformations on the dataset, the transformed dataset.

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