MLchartDataset catalogue

Patent · US12081323B2 · B2 · US

Techniques to control system updates and configuration changes via the cloud

(11) Publication number
US12081323B2
(21) Application number
18/116,957
(22) Filing date
2023-03-03
(30) Priority date
2016-07-22
(43) Publication date
2024-09-03
(45) Date of grant
2024-09-03
(51) IPC
B25J 15/00; B65G 1/04; G02B 6/38; G02B 6/42; G02B 6/44; G05D 23/19; G05D 23/20; G06F 1/18; G06F 1/20; G06F 11/14; G06F 11/34; G06F 12/0862; G06F 12/0893; G06F 12/10; G06F 12/109; G06F 12/14; G06F 13/16; G06F 13/40; G06F 13/42; G06F 15/16; G06F 15/80; G06F 16/901; G06F 3/06; G06F 8/65; G06F 9/30; G06F 9/38; G06F 9/4401; G06F 9/50; G06F 9/54; G06Q 10/06; G06Q 10/0631; G06Q 10/087; G06Q 10/20; G06Q 50/04; G07C 5/00; G08C 17/02; G11C 11/56; G11C 14/00; G11C 5/02; G11C 5/06; G11C 7/10; H03M 7/30; H03M 7/40; H04B 10/25; H04J 14/00; H04L 12/28; H04L 41/02; H04L 41/046; H04L 41/0813; H04L 41/082; H04L 41/0896; H04L 41/12; H04L 41/14; H04L 41/147; H04L 41/5019; H04L 43/065; H04L 43/08; H04L 43/0817; H04L 43/0876; H04L 43/0894; H04L 43/16; H04L 45/02; H04L 45/52; H04L 47/24; H04L 47/38; H04L 47/70; H04L 47/765; H04L 47/78; H04L 47/80; H04L 49/00; H04L 49/15; H04L 49/25; H04L 49/356; H04L 49/45; H04L 49/55; H04L 61/00; H04L 67/00; H04L 67/02; H04L 67/10; H04L 67/1004; H04L 67/1008; H04L 67/1012; H04L 67/1014; H04L 67/1029; H04L 67/1034; H04L 67/1097; H04L 67/12; H04L 67/306; H04L 67/51; H04L 69/04; H04L 69/329; H04L 9/06; H04L 9/14; H04L 9/32; H04Q 1/04; H04Q 11/00; H04W 4/02; H04W 4/80; H05K 1/02; H05K 1/18; H05K 13/04; H05K 5/02; H05K 7/14; H05K 7/20
(52) CPC
  • G06F Electric digital data processing: 3/061, 1/183, 1/20, 11/141, 11/3414, 12/0862, 12/0893, 12/10, 12/109, 12/1408, 13/161, 13/1668, 13/1694, 13/385, 13/4022, 13/4068, 13/409, 13/42, 13/4282, 15/161, 15/8061, 16/1748, 16/9014, 2209/483, 2209/5019, 2209/5022, 2212/1008, 2212/1024, 2212/1041, 2212/1044, 2212/152, 2212/202, 2212/401, 2212/402, 2212/7207, 3/0611, 3/0613, 3/0616, 3/0619, 3/0625, 3/0631, 3/0638, 3/064, 3/0647, 3/065, 3/0653, 3/0655, 3/0658, 3/0659, 3/0664, 3/0665, 3/067, 3/0673, 3/0679, 3/0683, 3/0688, 3/0689, 8/65, 9/30036, 9/3887, 9/4401, 9/4881, 9/5016, 9/5027, 9/5044, 9/505, 9/5072, 9/5077, 9/544
  • B25J Manipulators; chambers provided with manipulation devices: 15/0014
  • B65G Transport or storage devices, e.g. conveyors for loading or tipping, shop conveyor systems or pneumatic tube conveyors: 1/0492
  • G02B Optical elements, systems or apparatus: 6/3882, 6/3893, 6/3897, 6/4292, 6/4452
  • G05D Systems for controlling or regulating non-electric variables: 23/1921, 23/2039
  • G06Q Information and communication technology [ICT] specially adapted for administrative, commercial, financial, managerial or supervisory purposes; systems or methods specially adapted for administrative, commercial, financial, managerial or supervisory purposes, not otherwise provided for: 10/06, 10/06314, 10/087, 10/20, 50/04
  • G07C Time or attendance registers; registering or indicating the working of machines; generating random numbers; voting or lottery apparatus; arrangements, systems or apparatus for checking not provided for elsewhere: 5/008
  • G08C Transmission systems for measured values, control or similar signals: 17/02, 2200/00
  • G11C Static stores: 11/56, 14/0009, 5/02, 5/06, 7/1072
  • H03M Coding; decoding; code conversion in general: 7/30, 7/3084, 7/3086, 7/40, 7/4031, 7/4056, 7/4081, 7/6005, 7/6023
  • H04B Transmission: 10/25, 10/25891
  • H04J Multiplex communication: 14/00
  • H04L Transmission of digital information, e.g. telegraphic communication: 12/2809, 41/024, 41/046, 41/0813, 41/082, 41/0896, 41/12, 41/145, 41/147, 41/149, 41/40, 41/5019, 43/065, 43/08, 43/0817, 43/0876, 43/0894, 43/16, 45/02, 45/52, 47/24, 47/38, 47/765, 47/782, 47/805, 47/82, 47/823, 47/83, 49/00, 49/15, 49/25, 49/35, 49/357, 49/45, 49/555, 61/00, 67/02, 67/10, 67/1004, 67/1008, 67/1012, 67/1014, 67/1029, 67/1034, 67/1097, 67/12, 67/306, 67/34, 67/51, 69/04, 69/18, 69/329, 9/0643, 9/14, 9/3247, 9/3263
  • H04Q Selecting: 1/04, 1/09, 11/00, 11/0003, 11/0005, 11/0062, 11/0071, 2011/0037, 2011/0041, 2011/0052, 2011/0073, 2011/0079, 2011/0086, 2213/13523, 2213/13527
  • H04W Wireless communication networks: 4/023, 4/80
  • H05K Printed circuits; casings or constructional details of electric apparatus; manufacture of assemblages of electrical components: 1/0203, 1/181, 13/0486, 2201/066, 2201/10121, 2201/10159, 2201/10189, 5/0204, 7/1418, 7/1421, 7/1422, 7/1442, 7/1447, 7/1461, 7/1485, 7/1487, 7/1489, 7/1491, 7/1492, 7/1498, 7/2039, 7/20709, 7/20727, 7/20736, 7/20745, 7/20836
  • Y02D Climate change mitigation technologies in information and communication technologies [ICT], i.e. information and communication technologies aiming at the reduction of their own energy use: 10/00
  • Y02P Climate change mitigation technologies in the production or processing of goods: 90/30
  • Y04S Systems integrating technologies related to power network operation, communication or information technologies for improving the electrical power generation, transmission, distribution, management or usage, i.e. smart grids: 10/50, 10/52
  • Y10S Technical subjects covered by former uspc cross-reference art collections [xracs] and digests: 901/01, 901/30
(73) Assignee
Intel Corp
(72) Inventors
Murugasamy K. Nachimuthu; Mohan J. Kumar; Vasudevan Srinivasan
(54) Title
Techniques to control system updates and configuration changes via the cloud
(57) Abstract

Embodiments are generally directed apparatuses, methods, techniques and so forth determine an access level of operation based on an indication received via one or more network links from a pod management controller, and enable or disable a firmware update capability for a firmware device based on the access level of operation, the firmware update capability to change firmware for the firmware device. Embodiments may also include determining one or more configuration settings of a plurality of configuration settings to enable for configuration based on the access level of operation, and enable configuration of the one or more configuration settings.

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Claims (15)

  1. Cloud computing system for use in providing at least one cloud-based service associated with execution of at least one workload, the cloud computing system being configurable for use with remote rack server resources that are to communicate with the cloud computing system via optical communication links and at least one switch, the cloud computing system comprising: compute resources comprising at least one central processing unit and memory circuitry; storage resources for use in association with the compute resources; at least one optical fiber-based network for use in communicatively coupling at least certain of the compute resources and at least certain of the storage resources with the remote rack server resources via the optical communication links and the at least one switch; management resources for use in allocating compute resources, the storage resources, and the remote rack server resources for use in the execution of the at least one workload; wherein: the at least one workload comprises at least one virtual machine workload and/or is implemented using at least one virtualization environment; the compute resources and the storage resources are comprised in at least one cloud computing server; the remote rack server resources are comprised in at least one rack server that is remote from the at least one cloud computing server; the at least one rack server is to be communicatively coupled to the management resources via the optical communication links, the at least one switch, and the at least one optical fiber-based network; the management resources are configurable to obtain rack server resource utilization data from the remote rack server resources for use in the allocating of the remote rack server resources; the management resources are configurable to dynamically reallocate, based upon past resource utilization data, resource utilization prediction data, and machine-learning, the compute resources, the storage resources, and/or the remote rack server resources for use in the execution of the at least one workload; the at least one switch is to process communication that is in accordance with multiple link-layer protocols to enable dynamic allocation and/or dynamic reallocation of at least certain of the compute resources, the storage resources, and/or the remote rack server resources for use in the execution of the at least one workload; and the multiple-link layer protocols are different from each other, at least in part.
  2. The cloud computing system of claim 1, wherein: the compute resources, accelerator resources, and the storage resources are comprised, at least in part, in one or more pools of resources for being dynamically allocated based upon the resource utilization data.
  3. The cloud computing system of claim 2, wherein: the management resources are configurable to dynamically reallocate, based upon the past resource utilization data, the resource utilization prediction data, and the machine-learning, the compute resources, the storage resources, and the remote rack server resources for use in the execution of the at least one workload.
  4. The cloud computing system of claim 3, wherein: the cloud computing system is configurable to use telemetry data from the compute resources, the storage resources, and/or the remote rack server resources in capacity planning and/or management related to the compute resources, the storage resources, and/or the remote rack server resources.
  5. The cloud computing system of claim 4, wherein: the cloud computing system comprises at least one data center; and the at least one data center comprises the compute resources and the storage resources.
  6. At least one non-transitory machine-readable memory storing instructions for being executed by circuitry associated with a cloud computing system, the cloud computing system being for use in providing at least one cloud-based service associated with execution of at least one workload, the cloud computing system being configurable for use with remote rack server resources that are to communicate with the cloud computing system via optical communication links and at least one switch, the cloud computing system including compute resources, storage resources, at least one optical fiber-based network, and management resources, the instructions, when executed by the circuitry, resulting in the cloud computing system being configured for performance of operations comprising: allocating, by the management resources, the compute resources, the storage resources, and the remote rack server resources for use in the execution of the at least one workload; wherein: the compute resources comprise at least one central processing unit and memory circuitry; the storage resources are for use in association with the compute resources; the at least one optical fiber-based network is for use in communicatively coupling at least certain of the compute resources and at least certain of the storage resources with the remote rack server resources via the optical communication links and the at least one switch; the at least one workload comprises at least one virtual machine workload and/or is implemented using at least one virtualization environment; the compute resources and the storage resources are comprised in at least one cloud computing server; the remote rack server resources are comprised in at least one rack server that is remote from the at least one cloud computing server; the at least one rack server is to be communicatively coupled to the management resources via the optical communication links, the at least one switch, and the at least one optical fiber-based network; the management resources are configurable to obtain rack server resource utilization data from the remote rack server resources for use in the allocating of the remote rack server resources; the management resources are configurable to dynamically reallocate, based upon past resource utilization data, resource utilization prediction data, and machine-learning, the compute resources, the storage resources, and/or the remote rack server resources for use in the execution of the at least one workload; the at least one switch is to process communication that is in accordance with multiple link-layer protocols to enable dynamic allocation and/or dynamic reallocation of at least certain of the compute resources, the storage resources, and/or the remote rack server resources for use in the execution of the at least one workload: and the multiple-link layer protocols are different from each other, at least in part.
  7. The at least one non-transitory machine-readable memory of claim 6, wherein: the compute resources, the accelerator resources, and the storage resources are comprised, at least in part, in one or more pools of resources for being dynamically allocated based upon the resource utilization data.
  8. The at least one non-transitory machine-readable memory of claim 7, wherein: the management resources are configurable to dynamically reallocate, based upon the past resource utilization data, the resource utilization prediction data, and the machine-learning, the compute resources, the storage resources, and the remote rack server resources for use in the execution of the at least one workload.
  9. The at least one non-transitory machine-readable memory of claim 8, wherein: the cloud computing system is configurable to use telemetry data from the compute resources, the storage resources, and/or the remote rack server resources in capacity planning and/or management related to the compute resources, the storage resources, and/or the remote rack server resources.
  10. The at least one non-transitory machine-readable memory of claim 9, wherein: the cloud computing system comprises at least one data center; and the at least one data center comprises the compute resources and the storage resources.
  11. A method implemented using a cloud computing system, the cloud computing system being for use in providing at least one cloud-based service associated with execution of at least one workload, the cloud computing system being configurable for use with remote rack server resources that are to communicate with the cloud computing system via optical communication links and at least one switch, the cloud computing system including compute resources, storage resources, at least one optical fiber-based network, and management resources, the method comprising: allocating, by the management resources, the compute resources, the storage resources, and the remote rack server resources for use in the execution of the at least one workload; wherein: the compute resources comprise at least one central processing unit and memory circuitry; the storage resources are for use in association with the compute resources; the at least one optical fiber-based network is for use in communicatively coupling at least certain of the compute resources and at least certain of the storage resources with the remote rack server resources via the optical communication links and the at least one switch; the at least one workload comprises at least one virtual machine workload and/or is implemented using at least one virtualization environment; the compute resources and the storage resources are comprised in at least one cloud computing server; the remote rack server resources are comprised in at least one rack server that is remote from the at least one cloud computing server; the at least one rack server is to be communicatively coupled to the management resources via the optical communication links, the at least one switch, and the at least one optical fiber-based network; the management resources are configurable to obtain rack server resource utilization data from the remote rack server resources for use in the allocating of the remote rack server resources; the management resources are configurable to dynamically reallocate, based upon past resource utilization data, resource utilization prediction data, and machine-learning, the compute resources, the storage resources, and/or the remote rack server resources for use in the execution of the at least one workload; the at least one switch is to process communication that is in accordance with multiple link-layer protocols to enable dynamic allocation and/or dynamic reallocation of at least certain of the compute resources, the storage resources, and/or the remote rack server resources for use in the execution of the at least one workload: and the multiple-link layer protocols are different from each other, at least in part.
  12. The method of claim 11, wherein: the compute resources, accelerator resources, and the storage resources are comprised, at least in part, in one or more pools of resources for being dynamically allocated based upon the resource utilization data.
  13. The method of claim 12, wherein: the management resources are configurable to dynamically reallocate, based upon the past resource utilization data, the resource utilization prediction data, and the machine-learning, the compute resources, the storage resources, and the remote rack server resources for use in the execution of the at least one workload.
  14. The method of claim 13, wherein: the cloud computing system is configurable to use telemetry data from the compute resources, the storage resources, and/or the remote rack server resources in capacity planning and/or management related to the compute resources, the storage resources, and/or the remote rack server resources.
  15. The method of claim 14, wherein: the cloud computing system comprises at least one data center; and the at least one data center comprises the compute resources and the storage resources.

Description

This application is a continuation of prior co-pending U.S. patent application Ser. No. 15/396,014, filed Dec. 30, 2016, entitled “Techniques To Control System Updates And Configuration Changes Via The Cloud”, which claims the benefit of and priority to prior U.S. Provisional Patent Application No. 62/365,969, filed Jul. 22, 2016, prior U.S. Provisional Patent Application No. 62/376,859, filed Aug. 18, 2016, and prior U.S. Provisional Patent Application No. 62/427,268, filed Nov. 29, 2016. Each of these prior U.S. Patent Applications is hereby incorporated herein by reference in its entirety.

Embodiments described herein generally include performing circuit switching for workloads.

A computing data center may include one or more computing systems including a plurality of compute nodes that may include various compute structures (e.g., servers or sleds) and may be physically located on multiple racks. The sleds may include a number of physical resources interconnected via one or more compute structures and buses. Typically, a computing data center and components therein may require updating and configuration changes to fix potential problems and to provide physical resources in a desirable configuration for the users. However, current solutions may permit users to make updates and configuration changes in such a way that may be harmful to the data center, either intentionally or unintentionally. Thus, embodiments may address these and other issues as discussed herein.

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Record as JSON 
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  "publication_number": "US12081323B2",
  "country": "US",
  "kind": "B2",
  "title": "Techniques to control system updates and configuration changes via the cloud",
  "abstract": "Embodiments are generally directed apparatuses, methods, techniques and so forth determine an access level of operation based on an indication received via one or more network links from a pod management controller, and enable or disable a firmware update capability for a firmware device based on the access level of operation, the firmware update capability to change firmware for the firmware device. Embodiments may also include determining one or more configuration settings of a plurality of configuration settings to enable for configuration based on the access level of operation, and enable configuration of the one or more configuration settings.",
  "claims": [
    "1. Cloud computing system for use in providing at least one cloud-based service associated with execution of at least one workload, the cloud computing system being configurable for use with remote rack server resources that are to communicate with the cloud computing system via optical communication links and at least one switch, the cloud computing system comprising: compute resources comprising at least one central processing unit and memory circuitry; storage resources for use in association with the compute resources; at least one optical fiber-based network for use in communicatively coupling at least certain of the compute resources and at least certain of the storage resources with the remote rack server resources via the optical communication links and the at least one switch; management resources for use in allocating compute resources, the storage resources, and the remote rack server resources for use in the execution of the at least one workload; wherein: the at least one workload comprises at least one virtual machine workload and/or is implemented using at least one virtualization environment; the compute resources and the storage resources are comprised in at least one cloud computing server; the remote rack server resources are comprised in at least one rack server that is remote from the at least one cloud computing server; the at least one rack server is to be communicatively coupled to the management resources via the optical communication links, the at least one switch, and the at least one optical fiber-based network; the management resources are configurable to obtain rack server resource utilization data from the remote rack server resources for use in the allocating of the remote rack server resources; the management resources are configurable to dynamically reallocate, based upon past resource utilization data, resource utilization prediction data, and machine-learning, the compute resources, the storage resources, and/or the remote rack server resources for use in the execution of the at least one workload; the at least one switch is to process communication that is in accordance with multiple link-layer protocols to enable dynamic allocation and/or dynamic reallocation of at least certain of the compute resources, the storage resources, and/or the remote rack server resources for use in the execution of the at least one workload; and the multiple-link layer protocols are different from each other, at least in part.",
    "2. The cloud computing system of claim 1, wherein: the compute resources, accelerator resources, and the storage resources are comprised, at least in part, in one or more pools of resources for being dynamically allocated based upon the resource utilization data.",
    "3. The cloud computing system of claim 2, wherein: the management resources are configurable to dynamically reallocate, based upon the past resource utilization data, the resource utilization prediction data, and the machine-learning, the compute resources, the storage resources, and the remote rack server resources for use in the execution of the at least one workload.",
    "4. The cloud computing system of claim 3, wherein: the cloud computing system is configurable to use telemetry data from the compute resources, the storage resources, and/or the remote rack server resources in capacity planning and/or management related to the compute resources, the storage resources, and/or the remote rack server resources.",
    "5. The cloud computing system of claim 4, wherein: the cloud computing system comprises at least one data center; and the at least one data center comprises the compute resources and the storage resources.",
    "6. At least one non-transitory machine-readable memory storing instructions for being executed by circuitry associated with a cloud computing system, the cloud computing system being for use in providing at least one cloud-based service associated with execution of at least one workload, the cloud computing system being configurable for use with remote rack server resources that are to communicate with the cloud computing system via optical communication links and at least one switch, the cloud computing system including compute resources, storage resources, at least one optical fiber-based network, and management resources, the instructions, when executed by the circuitry, resulting in the cloud computing system being configured for performance of operations comprising: allocating, by the management resources, the compute resources, the storage resources, and the remote rack server resources for use in the execution of the at least one workload; wherein: the compute resources comprise at least one central processing unit and memory circuitry; the storage resources are for use in association with the compute resources; the at least one optical fiber-based network is for use in communicatively coupling at least certain of the compute resources and at least certain of the storage resources with the remote rack server resources via the optical communication links and the at least one switch; the at least one workload comprises at least one virtual machine workload and/or is implemented using at least one virtualization environment; the compute resources and the storage resources are comprised in at least one cloud computing server; the remote rack server resources are comprised in at least one rack server that is remote from the at least one cloud computing server; the at least one rack server is to be communicatively coupled to the management resources via the optical communication links, the at least one switch, and the at least one optical fiber-based network; the management resources are configurable to obtain rack server resource utilization data from the remote rack server resources for use in the allocating of the remote rack server resources; the management resources are configurable to dynamically reallocate, based upon past resource utilization data, resource utilization prediction data, and machine-learning, the compute resources, the storage resources, and/or the remote rack server resources for use in the execution of the at least one workload; the at least one switch is to process communication that is in accordance with multiple link-layer protocols to enable dynamic allocation and/or dynamic reallocation of at least certain of the compute resources, the storage resources, and/or the remote rack server resources for use in the execution of the at least one workload: and the multiple-link layer protocols are different from each other, at least in part.",
    "7. The at least one non-transitory machine-readable memory of claim 6, wherein: the compute resources, the accelerator resources, and the storage resources are comprised, at least in part, in one or more pools of resources for being dynamically allocated based upon the resource utilization data.",
    "8. The at least one non-transitory machine-readable memory of claim 7, wherein: the management resources are configurable to dynamically reallocate, based upon the past resource utilization data, the resource utilization prediction data, and the machine-learning, the compute resources, the storage resources, and the remote rack server resources for use in the execution of the at least one workload.",
    "9. The at least one non-transitory machine-readable memory of claim 8, wherein: the cloud computing system is configurable to use telemetry data from the compute resources, the storage resources, and/or the remote rack server resources in capacity planning and/or management related to the compute resources, the storage resources, and/or the remote rack server resources.",
    "10. The at least one non-transitory machine-readable memory of claim 9, wherein: the cloud computing system comprises at least one data center; and the at least one data center comprises the compute resources and the storage resources.",
    "11. A method implemented using a cloud computing system, the cloud computing system being for use in providing at least one cloud-based service associated with execution of at least one workload, the cloud computing system being configurable for use with remote rack server resources that are to communicate with the cloud computing system via optical communication links and at least one switch, the cloud computing system including compute resources, storage resources, at least one optical fiber-based network, and management resources, the method comprising: allocating, by the management resources, the compute resources, the storage resources, and the remote rack server resources for use in the execution of the at least one workload; wherein: the compute resources comprise at least one central processing unit and memory circuitry; the storage resources are for use in association with the compute resources; the at least one optical fiber-based network is for use in communicatively coupling at least certain of the compute resources and at least certain of the storage resources with the remote rack server resources via the optical communication links and the at least one switch; the at least one workload comprises at least one virtual machine workload and/or is implemented using at least one virtualization environment; the compute resources and the storage resources are comprised in at least one cloud computing server; the remote rack server resources are comprised in at least one rack server that is remote from the at least one cloud computing server; the at least one rack server is to be communicatively coupled to the management resources via the optical communication links, the at least one switch, and the at least one optical fiber-based network; the management resources are configurable to obtain rack server resource utilization data from the remote rack server resources for use in the allocating of the remote rack server resources; the management resources are configurable to dynamically reallocate, based upon past resource utilization data, resource utilization prediction data, and machine-learning, the compute resources, the storage resources, and/or the remote rack server resources for use in the execution of the at least one workload; the at least one switch is to process communication that is in accordance with multiple link-layer protocols to enable dynamic allocation and/or dynamic reallocation of at least certain of the compute resources, the storage resources, and/or the remote rack server resources for use in the execution of the at least one workload: and the multiple-link layer protocols are different from each other, at least in part.",
    "12. The method of claim 11, wherein: the compute resources, accelerator resources, and the storage resources are comprised, at least in part, in one or more pools of resources for being dynamically allocated based upon the resource utilization data.",
    "13. The method of claim 12, wherein: the management resources are configurable to dynamically reallocate, based upon the past resource utilization data, the resource utilization prediction data, and the machine-learning, the compute resources, the storage resources, and the remote rack server resources for use in the execution of the at least one workload.",
    "14. The method of claim 13, wherein: the cloud computing system is configurable to use telemetry data from the compute resources, the storage resources, and/or the remote rack server resources in capacity planning and/or management related to the compute resources, the storage resources, and/or the remote rack server resources.",
    "15. The method of claim 14, wherein: the cloud computing system comprises at least one data center; and the at least one data center comprises the compute resources and the storage resources."
  ],
  "description_excerpt": "This application is a continuation of prior co-pending U.S. patent application Ser. No. 15/396,014, filed Dec. 30, 2016, entitled “Techniques To Control System Updates And Configuration Changes Via The Cloud”, which claims the benefit of and priority to prior U.S. Provisional Patent Application No. 62/365,969, filed Jul. 22, 2016, prior U.S. Provisional Patent Application No. 62/376,859, filed Aug. 18, 2016, and prior U.S. Provisional Patent Application No. 62/427,268, filed Nov. 29, 2016. Each of these prior U.S. Patent Applications is hereby incorporated herein by reference in its entirety.\n\nEmbodiments described herein generally include performing circuit switching for workloads.\n\nA computing data center may include one or more computing systems including a plurality of compute nodes that may include various compute structures (e.g., servers or sleds) and may be physically located on multiple racks. The sleds may include a number of physical resources interconnected via one or more compute structures and buses. Typically, a computing data center and components therein may require updating and configuration changes to fix potential problems and to provide physical resources in a desirable configuration for the users. However, current solutions may permit users to make updates and configuration changes in such a way that may be harmful to the data center, either intentionally or unintentionally. Thus, embodiments may address these and other issues as discussed herein.",
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  "assignees": [
    "Intel Corp"
  ],
  "inventors": [
    "Murugasamy K. Nachimuthu",
    "Mohan J. Kumar",
    "Vasudevan Srinivasan"
  ],
  "filing_date": "2023-03-03",
  "publication_date": "2024-09-03",
  "grant_date": "2024-09-03",
  "priority_date": "2016-07-22",
  "application_number": "US-202318116957-A",
  "family_id": "60804962",
  "cited_by_count": 0,
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Record 384 of 8,000 in Patents full text (MLC-0201). Request the full dataset.