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公开(公告)号：US11249659B2
公开(公告)日：2022-02-15
申请号：US16861511
申请日：2020-04-29
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mayukh Dutta , Manoj Srivatsav , Soumen Shekhar Das , Gautham Parameshwar Hegde , Sivasakthi Thirugnanapandi
Abstract: In some examples, a system aggregates operational metric data of a plurality of storage volumes into aggregated operational metric data groups that correspond to different workload types of workloads for accessing data of a storage system. The system computes an operational metric for a first workload type of the different workload types, the operational metric relating to a resource of the storage system, where the computing of the operational metric for the first workload type comprises inputting aggregated operational metric data of a first aggregated operational metric data group of the aggregated operational metric data groups into a model trained at a system level of the storage system.
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公开(公告)号：US20240319885A1
公开(公告)日：2024-09-26
申请号：US18677326
申请日：2024-05-29
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mayukh Dutta , Aesha Dhar Roy , Manoj Srivatsav , Ganesha Devadiga , Geethanjali N. Rao , Prasenjit Saha , Jharna Aggarwal
CPC classification number: G06F3/0613 , G06F3/0659 , G06F3/067 , G06N20/00
Abstract: In some examples, a system creates a training data set based on features of sample workloads, the training data set comprising labels associated with the features of the sample workloads, where the labels are based on load indicators generated in a computing environment relating to load conditions of the computing environment resulting from execution of the sample workloads. The system groups selected workloads into a plurality of workload clusters based on features of the selected workloads, and computes, using a model trained based on the training data set, parameters representing contributions of respective workload clusters of the plurality of workload clusters to a load in the computing environment. The system performs workload management in the computing environment based on the computed parameters.
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公开(公告)号：US20240195864A1
公开(公告)日：2024-06-13
申请号：US18418424
申请日：2024-01-22
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mayukh Dutta , Manoj Srivatsav
IPC: H04L67/1008 , G06F11/34 , G06N3/045 , H04L67/1027 , H04L67/1029
CPC classification number: H04L67/1008 , G06F11/3428 , G06N3/045 , H04L67/1027 , H04L67/1029
Abstract: In some examples, a system receives a first collection of tokens relating to characteristics of workloads for a computing system. The system encodes the first collection of tokens, the encoding including computing weights representing relationships among tokens of the first collection of tokens, and generating a representation of the first collection of tokens based on the weights. The system determines, based on the representation, a correlation between the first collection of tokens and a second collection of tokens relating to elapsed times in executing the workloads.
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公开(公告)号：US11704022B2
公开(公告)日：2023-07-18
申请号：US17649901
申请日：2022-02-03
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mayukh Dutta , Manoj Srivatsav , Soumen Shekhar Das , Gautham Parameshwar Hegde , Sivasakthi Thirugnanapandi
IPC: G06F3/06 , G06F9/50 , G06F18/214
CPC classification number: G06F3/061 , G06F3/0604 , G06F3/067 , G06F3/0631 , G06F3/0653 , G06F3/0683 , G06F9/5011 , G06F18/214
Abstract: In some examples, a system aggregates operational metric data of a plurality of storage volumes into aggregated operational metric data groups that correspond to different workload types of workloads for accessing data of a storage system. The system computes an operational metric for a first workload type of the different workload types, the operational metric relating to a resource of the storage system, where the computing of the operational metric for the first workload type comprises inputting aggregated operational metric data of a first aggregated operational metric data group of the aggregated operational metric data groups into a model trained at a system level of the storage system.
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公开(公告)号：US20220398021A1
公开(公告)日：2022-12-15
申请号：US17303883
申请日：2021-06-09
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Mayukh Dutta , Aesha Dhar Roy , Manoj Srivatsav , Ganesha Devadiga , Geethanjali N. Rao , Prasenjit Saha , Jharna Aggarwal
Abstract: In some examples, a system creates a training data set based on features of sample workloads, the training data set comprising labels associated with the features of the sample workloads, where the labels are based on load indicators generated in a computing environment relating to load conditions of the computing environment resulting from execution of the sample workloads. The system groups selected workloads into a plurality of workload clusters based on features of the selected workloads, and computes, using a model trained based on the training data set, parameters representing contributions of respective workload clusters of the plurality of workload clusters to a load in the computing environment. The system performs workload management in the computing environment based on the computed parameters.
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Patent Agency Ranking
公开(公告)号：US20220155979A1
公开(公告)日：2022-05-19
申请号：US17649901
申请日：2022-02-03
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mayukh Dutta , Manoj Srivatsav , Soumen Shekhar Das , Gautham Parameshwar Hegde , Sivasakthi Thirugnanapandi
Abstract: In some examples, a system aggregates operational metric data of a plurality of storage volumes into aggregated operational metric data groups that correspond to different workload types of workloads for accessing data of a storage system. The system computes an operational metric for a first workload type of the different workload types, the operational metric relating to a resource of the storage system, where the computing of the operational metric for the first workload type comprises inputting aggregated operational metric data of a first aggregated operational metric data group of the aggregated operational metric data groups into a model trained at a system level of the storage system.
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公开(公告)号：US20190334801A1
公开(公告)日：2019-10-31
申请号：US16034531
申请日：2018-07-13
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Mayukh Dutta , Manoj Srivatsav , John J. Sengenberger
Abstract: A system or method for identifying latency contributors in a data storage network, that may include creating a historical workload fingerprint model for a data storage network from training data, along with monitoring and classifying a current sample data from the data storage network into a cluster, current workload fingerprint, and current workload type. The method may further include assigning a score to the current sample data based on the historical workload fingerprint model and correlating measured latency values from the current sample data to historically measured latency related factors to create a latency score chart that identifies factors causing latency in the data storage network for the current sample data.
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公开(公告)号：US11882175B2
公开(公告)日：2024-01-23
申请号：US17649993
申请日：2022-02-04
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mayukh Dutta , Manoj Srivatsav
IPC: G06N3/045 , H04L67/1008 , H04L67/1027 , H04L67/1029 , G06F11/34
CPC classification number: H04L67/1008 , G06F11/3428 , G06N3/045 , H04L67/1027 , H04L67/1029
Abstract: In some examples, a system receives a first collection of tokens relating to characteristics of workloads for a computing system. The system encodes the first collection of tokens, the encoding including computing weights representing relationships among tokens of the first collection of tokens, and generating a representation of the first collection of tokens based on the weights. The system determines, based on the representation, a correlation between the first collection of tokens and a second collection of tokens relating to elapsed times in executing the workloads.
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公开(公告)号：US20230251785A1
公开(公告)日：2023-08-10
申请号：US17650426
申请日：2022-02-09
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Mayukh Dutta , Aesha Dhar Roy , Manoj Srivatsav
IPC: G06F3/06
CPC classification number: G06F3/0631 , G06F3/0604 , G06F3/0683
Abstract: In some examples, a system receives input information of characteristics relating to a storage volume to be provisioned in a collection of storage systems, determines, based on the input information of the characteristics relating to the storage volume, a workload profile, and simulates execution of a workload according to the workload profile in each storage system of the collection of storage systems. Based on the simulation, the system determines a respective amount of headroom used by the workload in each storage system of the collection of storage systems, and selects, based on the determined respective amounts of headroom used by the workload in respective storage systems of the collection of storage systems, a storage system from the collection of storage systems on which the storage volume is to be provisioned.
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公开(公告)号：US11481117B2
公开(公告)日：2022-10-25
申请号：US16861575
申请日：2020-04-29
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mayukh Dutta , Manoj Srivatsav , Gautham Parameshwar Hegde
Abstract: In some examples, a system assigns workload fingerprints to each respective storage volume of a plurality of storage volumes, the workload fingerprints assigned to the respective storage volume across a plurality of points. Based on the workload fingerprints assigned to respective storage volumes of the plurality of storage volumes, the system groups the storage volumes into clusters of storage volumes. The system manages an individual cluster of the clusters of storage volumes according to an attribute associated with the individual cluster.
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