公开(公告)号：US20240354218A1

公开(公告)日：2024-10-24

申请号：US18302279

申请日：2023-04-18

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： SRIDHAR BALACHANDRIAH ,  SATISH KUMAR MOPUR ,  LANCE MACKIMME EVANS ,  SHERIN THYIL GEORGE ,  KEVAN REHM

IPC: G06F11/34

CPC classification number: G06F11/3495 ,  G06F11/3433

Abstract: Systems and methods are provided for utilization of optimal data access interface usage in machine learning pipelines. Examples of the systems and methods disclosed herein include identifying data access interfaces comprising at least a first data access interface for a persistent storage distributed across a plurality of storage nodes and at least a second data access interface for an in-memory object store, and receiving, from a compute node, a data operation request as part of a machine learning pipeline. Additionally, performance metrics are obtained for the plurality of access interfaces, and based on a type of data operation request, the data operation is executed using a data access interface selected from the plurality of data access interface based on the performance metrics and providing an object handle to the compute node.

公开(公告)号：US20240345926A1

公开(公告)日：2024-10-17

申请号：US18756723

申请日：2024-06-27

Applicant: Capital One Services, LLC

Inventor： Emmanuel Obogbaimhe ,  Kadhiresan Kanniyappan ,  Krystan R. Franzen ,  Yasawy Rajendraprasad Ravala ,  Matthew Zheng ,  Matthew Blake Ackard

IPC: G06F11/14 ,  G06F11/30 ,  G06F11/34

CPC classification number: G06F11/142 ,  G06F11/3051 ,  G06F11/3428 ,  G06F11/3433

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of identifying at least one computing specification image within a plurality of computing specification images; monitoring each data agent within the plurality of preinstalled data agents for a predetermined period of time to establish a data agent usage baseline associated with each data agent within the plurality of preinstalled data agents; utilizing a chaos engineering algorithm to dynamically perturb each data agent; calculating a usage test score for each data agent within the plurality of preinstalled data agents; calculating an overall data agent-specific usage score associated with each data agent within the plurality of preinstalled data agents based on the plurality of data agent-specific usage test scores; and rejecting at least one data agent within the plurality of preinstalled data agents from being utilized to launch the instance of the software application.

公开(公告)号：US12112201B2

公开(公告)日：2024-10-08

申请号：US17568567

申请日：2022-01-04

Applicant: Intel Corporation

Inventor： Kshitij Doshi ,  Francesc Guim Bernat ,  Timothy Verrall ,  Ned Smith ,  Rajesh Gadiyar

IPC: H04L9/32 ,  G06F8/41 ,  G06F9/445 ,  G06F9/50 ,  G06F9/54 ,  G06F11/34 ,  G06F16/18 ,  G06F21/60 ,  H04L9/00 ,  H04L9/06 ,  H04L9/08 ,  H04L9/40 ,  H04L41/0893 ,  H04L41/0896 ,  H04L41/14 ,  H04L41/142 ,  H04L41/5009 ,  H04L41/5025 ,  H04L41/5051 ,  H04L43/08 ,  H04L47/70 ,  H04L67/1008 ,  H04L67/12 ,  H04L67/141 ,  G06F9/38 ,  G06F9/455 ,  G06F9/48 ,  G06F11/10 ,  G06F12/14 ,  G06F16/23 ,  G16Y40/10 ,  H04L67/10

CPC classification number: G06F9/5016 ,  G06F8/443 ,  G06F9/44594 ,  G06F9/505 ,  G06F9/5072 ,  G06F9/5077 ,  G06F9/544 ,  G06F11/3433 ,  G06F16/1865 ,  G06F21/602 ,  H04L9/008 ,  H04L9/0637 ,  H04L9/0822 ,  H04L9/0825 ,  H04L9/0866 ,  H04L41/0893 ,  H04L41/0896 ,  H04L41/142 ,  H04L41/145 ,  H04L41/5009 ,  H04L41/5025 ,  H04L41/5051 ,  H04L43/08 ,  H04L47/822 ,  H04L63/0407 ,  H04L63/0428 ,  H04L63/1408 ,  H04L63/20 ,  H04L67/1008 ,  H04L67/12 ,  H04L67/141 ,  G06F9/3836 ,  G06F9/45533 ,  G06F9/4881 ,  G06F9/5038 ,  G06F11/1004 ,  G06F12/1408 ,  G06F16/2322 ,  G06F2209/509 ,  G16Y40/10 ,  H04L9/3297 ,  H04L67/10

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to aggregate telemetry data in an edge environment. An example apparatus includes at least one processor, and memory including instructions that, when executed, cause the at least one processor to at least generate a composition for an edge service in the edge environment, the composition representative of a first interface to obtain the telemetry data, the telemetry data associated with resources of the edge service and including a performance metric, generate a resource object based on the performance metric, generate a telemetry object based on the performance metric, and generate a telemetry executable based on the composition, the composition including at least one of the resource object or the telemetry object, the telemetry executable to generate the telemetry data in response to the edge service executing a computing task distributed to the edge service based on the telemetry data.

公开(公告)号：US12106151B2

公开(公告)日：2024-10-01

申请号：US17157896

申请日：2021-01-25

Applicant: LENOVO (Singapore) PTE. LTD.

Inventor： Saba Shah ,  Xiaohua Xu ,  Rod D. Waltermann

IPC: G06F9/50 ,  G06F11/30 ,  G06F11/34 ,  G06N20/00

CPC classification number: G06F9/5038 ,  G06F9/5044 ,  G06F9/505 ,  G06F11/3409 ,  G06F11/3433 ,  G06N20/00 ,  G06F11/3003 ,  G06F2209/501 ,  G06F2209/509

Abstract: An apparatus includes a processor and a memory that stores code executable by the processor. The code is executable by the processor to receive a request at a first device to execute a machine learning workload for the first device, dynamically determine at least one characteristic of the first device that is related to execution of the machine learning workload, dynamically determine at least one characteristic of a second device that is related to execution of the machine learning workload, and select one of the first and second devices to execute the machine learning workload in response to the at least one characteristic of the selected one of the first and second devices being more suitable for execution of the machine learning workload than another of the first and second devices.

公开(公告)号：US12093742B2

公开(公告)日：2024-09-17

申请号：US18477357

申请日：2023-09-28

Applicant: BANK OF AMERICA CORPORATION

Inventor： Naga Vamsi Krishna Akkapeddi

IPC: G06F9/50 ,  G06F11/34 ,  G06F16/21 ,  G06N20/00

CPC classification number: G06F9/505 ,  G06F9/5027 ,  G06F11/3433 ,  G06F16/219 ,  G06N20/00 ,  G06F9/50 ,  G06F9/5011 ,  G06F9/5016 ,  G06F9/5044 ,  G06F2209/5019

Abstract: A system includes a subsystem, a database, a memory, and a processor. The subsystem includes a computational resource associated with a resource usage and having a capacity corresponding to a maximum resource usage value. The database stores training data that includes historical resource usages and historical events. The memory stores a machine learning algorithm that is trained, based on the training data, to predict, based on the occurrence of an event, that a future value of the resource usage at a future time will be greater than the maximum value. The processor detects that the event has occurred. In response, the processor applies the machine learning algorithm to predict that the future value of the resource usage will be greater than the maximum value. Prior to the future time, the processor increases the capacity of the computational resource to accommodate the future value of the resource usage.

公开(公告)号：US12056129B2

公开(公告)日：2024-08-06

申请号：US18113154

申请日：2023-02-23

Applicant: Hitachi, Ltd.

Inventor： Mayuko Ozawa ,  Satoru Watanabe ,  Norifumi Nishikawa ,  Kazuhiko Mogi

IPC: G06F16/30 ,  G06F11/34 ,  G06F16/22 ,  G06F16/2455

CPC classification number: G06F16/2456 ,  G06F11/3433 ,  G06F16/2255

Abstract: The processing load for joining a plurality of tables by hash join is reduced for a computer system in which the CPU of a node creates a partial bloom filter that manages a first table hash value of a joining key of a row corresponding to a query in an assigned row of a build table. An integrated bloom filter is created from a plurality of partial bloom filters, and a second table hash value of the joining key of the row corresponding to the condition of the query among the rows of a probe table is calculated. The row of the probe table is transmitted to the node containing a row of the build table of the join hash value for that row when the integrated bloom filter includes an identical first table hash value, and an integrated joined table is created and returned to the query request source.

公开(公告)号：US20240241701A1

公开(公告)日：2024-07-18

申请号：US18414136

申请日：2024-01-16

Applicant: DEEP FOREST SCIENCES, INC.

Inventor： BHARATH RAMSUNDAR ,  ARUN PALANIAPPAN TR

IPC: G06F8/36 ,  G06F11/34

CPC classification number: G06F8/36 ,  G06F11/3433

Abstract: Various aspects of the present disclosure relate to techniques for a cloud scientific machine learning programming environment. An apparatus includes at least one memory and at least one processor coupled to the memory and configured to cause the apparatus to receive a request to perform a machine learning task, analyze the machine learning task to determine one or more functions for performing the machine learning task, generate a workflow for the one or more functions of the machine learning task, execute the generated workflow, and provide results of the executed workflow.

公开(公告)号：US12038814B2

公开(公告)日：2024-07-16

申请号：US17703724

申请日：2022-03-24

Applicant: Commvault Systems, Inc.

Inventor： Henry Wallace Dornemann

IPC: G06F7/00 ,  G06F9/455 ,  G06F11/14 ,  G06F11/16 ,  G06F11/20 ,  G06F11/30 ,  G06F11/34 ,  G06F16/172 ,  G06F16/188 ,  G06F17/00

CPC classification number: G06F11/1464 ,  G06F9/45558 ,  G06F11/14 ,  G06F11/1469 ,  G06F11/1658 ,  G06F11/2094 ,  G06F11/3034 ,  G06F11/3055 ,  G06F11/3433 ,  G06F16/172 ,  G06F16/188 ,  G06F2009/4557 ,  G06F2009/45575 ,  G06F11/1453 ,  G06F2201/815

Abstract: Uploads of restored virtual machine (“VM”) data to cloud storage, e.g., VM restore-to-cloud operations, are performed without having to write whole restored virtual disk files to a proxy server before the virtual disk data begins uploading to cloud. Restored data blocks from a backup source are locally cached, staged for efficiency, and asynchronously uploaded to the cloud page-by-page without tapping mass storage resources on the proxy. Downloads of VM data from cloud storage, e.g., VM backup-from-cloud, are performed without having to download a virtual disk file in its entirety to the proxy server before the backup operation begins generating a backup copy. This speeds up “pulling” VM data from the cloud by pre-fetching and locally caching downloaded data blocks. The cached data blocks are processed for backup and stored page-by-page directly into a secondary copy of the cloud VM virtual-disk file without tapping mass storage resource at the proxy.

公开(公告)号：US12034640B2

公开(公告)日：2024-07-09

申请号：US17025832

申请日：2020-09-18

Applicant: Huawei Cloud Computing Technologies Co., Ltd.

Inventor： Weihua Shan ,  Xuliang Li

IPC: G06F15/16 ,  G06F9/50 ,  G06F11/07 ,  G06F11/34 ,  H04L41/0803 ,  H04L47/10 ,  H04L47/12

CPC classification number: H04L47/10 ,  G06F9/5061 ,  G06F9/5083 ,  G06F11/0745 ,  G06F11/076 ,  G06F11/3409 ,  G06F11/3433 ,  H04L41/0803 ,  H04L47/12 ,  G06F2201/81

Abstract: A data processing method is provided, including: sending, by an operation node, an alarm signal to a control node when a monitor detects that processing performance of data from a first data transmission pipe is lower than a first threshold (S102), where the alarm signal is used to indicate that the processing performance of the data from the first data transmission pipe is low; and when receiving the alarm signal, reducing, by the control node, a data amount that is from the first data transmission pipe and that is allocated to the operation node (S103). The solution can reduce fluctuation in processing performance of the data processing system during traffic control.

公开(公告)号：US12010169B2

公开(公告)日：2024-06-11

申请号：US18062614

申请日：2022-12-07

Applicant: Capital One Services, LLC

Inventor： Christian Bartram ,  Connor Cason ,  Noriaki Tatsumi

IPC: H04L67/1029 ,  G06F11/30 ,  G06F11/34 ,  H04L67/1008 ,  H04L67/1012

CPC classification number: H04L67/1029 ,  G06F11/3006 ,  G06F11/3433 ,  H04L67/1008 ,  H04L67/1012

Abstract: In some implementations, a system may monitor session data associated with a first module and a second module of a platform. The system may determine a rate of communication between the first module and the second module based on the session data. The system may determine, using an optimization model, a co-location score associated with the first module and the second module based on the rate of communication, wherein the co-location score indicates an impact of co-location of the first module and the second module. The system may determine that the co-location score satisfies a co-location score threshold associated with an improvement to an operation of the platform. The system may perform an action associated with co-locating the first module and the second module.