公开(公告)号：US10671434B1

公开(公告)日：2020-06-02

申请号：US16040846

申请日：2018-07-20

Applicant: PURE STORAGE, INC.

Inventor： Brian Gold ,  Emily Watkins ,  Ivan Jibaja ,  Igor Ostrovsky ,  Roy Kim

IPC: G06F3/06 ,  G06F9/50 ,  G06N3/08 ,  G06T1/20 ,  G06F9/48 ,  G06N3/063 ,  G06T1/60

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.

公开(公告)号：US10915813B2

公开(公告)日：2021-02-09

申请号：US16449241

申请日：2019-06-21

Applicant: Pure Storage, Inc.

Inventor： Fabio Margaglia ,  Emily Watkins ,  Hari Kannan ,  Cary A. Sandvig

IPC: G06N3/08 ,  G06N5/04

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.

公开(公告)号：US10360214B2

公开(公告)日：2019-07-23

申请号：US16045814

申请日：2018-07-26

Applicant: PURE STORAGE, INC.

Inventor： Brian Gold ,  Emily Watkins ,  Ivan Jibaja ,  Igor Ostrovsky ,  Roy Kim

IPC: G06F16/00 ,  G06F16/2453 ,  G06F3/06 ,  G06F16/22 ,  G06N20/00 ,  G06N3/08 ,  G06T1/20 ,  G06T1/60

Abstract: Ensuring reproducibility in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: identifying, by a unified management plane, one or more transformations applied to a dataset by the artificial intelligence infrastructure, wherein applying the one or more transformations to the dataset causes the artificial intelligence infrastructure to generate a transformed dataset; storing, within the one or more storage systems, information describing the dataset, the one or more transformations applied to the dataset, and the transformed dataset; identifying, by the unified management plane, one or more machine learning models executed by the artificial intelligence infrastructure using the transformed dataset as input; and storing, within the one or more storage systems, information describing one or more machine learning models executed using the transformed dataset as input.

公开(公告)号：US11768636B2

公开(公告)日：2023-09-26

申请号：US18146807

申请日：2022-12-27

Applicant: PURE STORAGE, INC.

Inventor： Brian Gold ,  Emily Watkins ,  Ivan Jibaja ,  Igor Ostrovsky ,  Roy Kim

IPC: H04L67/12 ,  G06F3/06 ,  G06N20/00 ,  G06F16/245 ,  G06F16/178 ,  G06Q30/0242 ,  G06F9/48 ,  G06F9/50 ,  G06N3/063 ,  G06N3/08 ,  G06T1/20 ,  G06T1/60 ,  G06F16/958 ,  G06F16/248

CPC classification number: G06F3/0679 ,  G06F3/0604 ,  G06F3/067 ,  G06F3/0608 ,  G06F3/0646 ,  G06F3/0649 ,  G06F9/4881 ,  G06F9/5027 ,  G06F16/1794 ,  G06F16/245 ,  G06N3/063 ,  G06N3/08 ,  G06N20/00 ,  G06Q30/0243 ,  G06T1/20 ,  G06T1/60 ,  G06F16/248 ,  G06F16/972 ,  G06T2200/28

Abstract: Generating a transformed dataset for use by a machine learning model in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: storing, within one or more storage systems, a transformed dataset generated by applying one or more transformations to a dataset that are identified based on one or more expected input formats of data received as input data by one or more machine learning models to be executed on one or more servers; and transmitting, from the one or more storage systems to the one or more servers without reapplying the one or more transformations on the dataset, the transformed dataset including data in the one or more expected formats of data to be received as input data by the one or more machine learning models.

公开(公告)号：US11556280B2

公开(公告)日：2023-01-17

申请号：US16888402

申请日：2020-05-29

Applicant: PURE STORAGE, INC.

Inventor： Brian Gold ,  Emily Watkins ,  Ivan Jibaja ,  Igor Ostrovsky ,  Roy Kim

IPC: G06F3/06 ,  G06N20/00 ,  G06F16/245 ,  G06F16/178 ,  G06Q30/02 ,  G06F9/48 ,  G06F9/50 ,  G06N3/063 ,  G06N3/08 ,  G06T1/20 ,  G06T1/60 ,  G06F16/958 ,  G06F16/248

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.

公开(公告)号：US11494692B1

公开(公告)日：2022-11-08

申请号：US16365648

申请日：2019-03-26

Applicant: PURE STORAGE, INC.

Inventor： Emily Watkins ,  Ramnath Sai Sagar Thumbavanam Padmanabhan ,  James Fisher ,  Harry Lydiksen

IPC: H04L67/1097 ,  G06N20/00 ,  G06T1/20 ,  H04L67/1087

Abstract: A hyperscale artificial intelligence and machine learning infrastructure includes a plurality of racks, where: at least one or more of the racks include one or more GPU servers; at least one or more of the racks include one or more storage systems; each of the racks include one or more switches coupled to at least one switch in another rack; and the one or more GPU servers are configured to execute one or more artificial intelligence or machine learning applications, wherein data stored within the one or more storage systems is used as input to the one or more artificial intelligence or machine learning applications.

公开(公告)号：US11010233B1

公开(公告)日：2021-05-18

申请号：US16249534

申请日：2019-01-16

Applicant: Pure Storage, Inc.

Inventor： Christopher Golden ,  Emily Watkins

IPC: G06F11/07 ,  G06F11/34 ,  G06N20/00 ,  G06N3/08

Abstract: An exemplary monitoring system receives log data associated with an operation of a hardware component, applies the log data as an input to an unsupervised machine learning model, and identifies, based on an output of the unsupervised machine learning model, an anomaly in the log data.

公开(公告)号：US10275285B1

公开(公告)日：2019-04-30

申请号：US16046337

申请日：2018-07-26

Applicant: PURE STORAGE, INC.

Inventor： Brian Gold ,  Emily Watkins ,  Ivan Jibaja ,  Igor Ostrovsky ,  Roy Kim

IPC: G06F9/50 ,  G06T1/60 ,  G06N3/063 ,  G06F9/48 ,  G06T1/20 ,  G06N3/08

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.

公开(公告)号：US12067466B2

公开(公告)日：2024-08-20

申请号：US17979467

申请日：2022-11-02

Applicant: PURE STORAGE, INC.

Inventor： Emily Watkins ,  Ramnath Sai Sagar Thumbavanam Padmanabhan ,  James Fisher ,  Harry Lydiksen

IPC: G06N20/00 ,  G06T1/20 ,  H04L67/1087 ,  H04L67/1097

CPC classification number: G06N20/00 ,  G06T1/20 ,  H04L67/1089 ,  H04L67/1097

Abstract: A hyperscale artificial intelligence and machine learning infrastructure includes a plurality of racks, where: at least one or more of the racks include one or more GPU servers; at least one or more of the racks include one or more storage systems; each of the racks include one or more switches coupled to at least one switch in another rack; and the one or more GPU servers are configured to execute one or more artificial intelligence or machine learning applications, wherein data stored within the one or more storage systems is used as input to the one or more artificial intelligence or machine learning applications.

公开(公告)号：US20230325272A1

公开(公告)日：2023-10-12

申请号：US18209789

申请日：2023-06-14

Applicant: Pure Storage, Inc.

Inventor： Christopher Golden ,  Emily Watkins

IPC: G06F11/07 ,  G06F11/34 ,  G06N3/088 ,  G06N20/00

CPC classification number: G06F11/079 ,  G06F11/3476 ,  G06N3/088 ,  G06F11/0793 ,  G06F11/0709 ,  G06N20/00 ,  G06F11/3409 ,  G06F2201/81 ,  G06F2201/86

Abstract: An illustrative method may include identifying, based on data associated with an operation of a hardware component, 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.