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Patent Agency Ranking
公开(公告)号：US11734097B1
公开(公告)日：2023-08-22
申请号：US17160053
申请日：2021-01-27
Applicant: Pure Storage, Inc.
Inventor： Christopher Golden , Emily Watkins
CPC classification number: G06F11/079 , G06F11/0709 , G06F11/0793 , G06F11/3409 , G06F11/3476 , G06N3/088 , G06N20/00 , G06F2201/81 , G06F2201/86
Abstract: An illustrative method includes identifying, based on an output of a machine learning model that receives data associated with an operation of a hardware component as an input, an anomaly in the data, determining that the anomaly is representative of an issue associated with the hardware component, and performing, based on the determining that the anomaly is representative of the issue associated with the hardware component, a remedial action that affects a performance of the operation of the hardware component.
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公开(公告)号：US10671435B1
公开(公告)日：2020-06-02
申请号：US16040996
申请日：2018-07-20
Applicant: PURE STORAGE, INC.
Inventor： Brian Gold , Emily Watkins , Ivan Jibaja , Igor Ostrovsky , Roy Kim
Abstract: 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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公开(公告)号：US10649988B1
公开(公告)日：2020-05-12
申请号：US16047649
申请日：2018-07-27
Applicant: PURE STORAGE, INC.
Inventor： Brian Gold , Emily Watkins , Ivan Jibaja , Igor Ostrovsky , Roy Kim
IPC: G06F16/245 , G06F16/248 , G06F16/958
Abstract: An artificial intelligence and machine learning infrastructure system, including: one or more storage systems comprising, respectively, one or more storage devices; and one or more graphical processing units, wherein the graphical processing units are configured to communicate with the one or more storage systems over a communication fabric; where the one or more storage systems, the one or more graphical processing units, and the communication fabric are implemented within a single chassis.
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公开(公告)号：US10467527B1
公开(公告)日：2019-11-05
申请号：US15885665
申请日：2018-01-31
Applicant: Pure Storage, Inc.
Inventor： Fabio Margaglia , Emily Watkins , Hari Kannan , Cary A. Sandvig
Abstract: An apparatus for artificial intelligence acceleration is provided. The apparatus includes a storage and compute system having a distributed, redundant key value store for metadata. The storage and compute system having distributed compute resources configurable to access, through a plurality of authorities, data in the solid-state memory, run inference with a deep learning model, generate vectors for the data and store the vectors in the key value store.
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公开(公告)号：US10275176B1
公开(公告)日：2019-04-30
申请号：US16046102
申请日：2018-07-26
Applicant: PURE STORAGE, INC.
Inventor： Brian Gold , Emily Watkins , Ivan Jibaja , Igor Ostrovsky , Roy Kim
Abstract: Data transformation offloading in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: storing, within the storage system, a dataset; identifying, in dependence upon one or more machine learning models to be executed on the GPU servers, one or more transformations to apply to the dataset; and generating, by the storage system in dependence upon the one or more transformations, a transformed dataset.
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