公开(公告)号：US20180309692A1

公开(公告)日：2018-10-25

申请号：US15872928

申请日：2018-01-16

Applicant: Intel Corporation

Inventor： Subramony Sesha ,  Archana Patni ,  Ananth S. Narayan ,  Mrittika Ganguli

IPC: H04L12/911 ,  G06F9/50 ,  H04L29/08 ,  G06F9/455 ,  H04L12/26

CPC classification number: H04L47/70 ,  G06F9/45504 ,  G06F9/5027 ,  G06F9/505 ,  H04L43/16 ,  H04L67/1095 ,  H04L67/1097 ,  H04L67/2842

Abstract: Technologies for contention-aware cloud compute scheduling include a number of compute nodes in a cloud computing cluster and a cloud controller. Each compute node collects performance data indicative of cache contention on the compute node, for example, cache misses per thousand instructions. Each compute node determines a contention score as a function of the performance data and stores the contention score in a cloud state database. In response to a request for a new virtual machine, the cloud controller receives contention scores for the compute nodes and selects a compute node based on the contention score. The cloud controller schedules the new virtual machine on the selected compute node. The contention score may include a contention metric and a contention score level indicative of the contention metric. The contention score level may be determined by comparing the contention metric to a number of thresholds. Other embodiments are described and claimed.

公开(公告)号：US20220029895A1

公开(公告)日：2022-01-27

申请号：US17494569

申请日：2021-10-05

Applicant: Intel Corporation

Inventor： Mrittika Ganguli ,  Muthuvel M. I ,  Ananth S. Narayan ,  Jaideep Moses ,  Andrew J. Herdrich ,  Rahul Khanna

IPC: H04L12/24

Abstract: In accordance with some embodiments, a cloud service provider may operate a data center in a way that dynamically reallocates resources across nodes within the data center based on both utilization and service level agreements. In other words, the allocation of resources may be adjusted dynamically based on current conditions. The current conditions in the data center may be a function of the nature of all the current workloads. Instead of simply managing the workloads in a way to increase overall execution efficiency, the data center instead may manage the workload to achieve quality of service requirements for particular workloads according to service level agreements.

公开(公告)号：US20200344175A1

公开(公告)日：2020-10-29

申请号：US16875597

申请日：2020-05-15

Applicant: Intel Corporation

Inventor： Subramony Sesha ,  Archana Patni ,  Ananth S. Narayan ,  Mrittika Ganguli

IPC: H04L12/911 ,  G06F9/50 ,  H04L29/08 ,  G06F9/455 ,  H04L12/26

Abstract: Technologies for contention-aware cloud compute scheduling include a number of compute nodes in a cloud computing cluster and a cloud controller. Each compute node collects performance data indicative of cache contention on the compute node, for example, cache misses per thousand instructions. Each compute node determines a contention score as a function of the performance data and stores the contention score in a cloud state database. In response to a request for a new virtual machine, the cloud controller receives contention scores for the compute nodes and selects a compute node based on the contention score. The cloud controller schedules the new virtual machine on the selected compute node. The contention score may include a contention metric and a contention score level indicative of the contention metric. The contention score level may be determined by comparing the contention metric to a number of thresholds. Other embodiments are described and claimed.

公开(公告)号：US20180212842A1

公开(公告)日：2018-07-26

申请号：US15926866

申请日：2018-03-20

Applicant: Intel Corporation

Inventor： Mrittika Ganguli ,  Muthuvel M. I ,  Ananth S. Narayan ,  Jaideep Moses ,  Andrew J. Herdrich ,  Rahul Khanna

IPC: H04L12/24

CPC classification number: H04L41/50 ,  H04L41/145 ,  H04L41/5009 ,  H04L41/5025

Abstract: In accordance with some embodiments, a cloud service provider may operate a data center in a way that dynamically reallocates resources across nodes within the data center based on both utilization and service level agreements. In other words, the allocation of resources may be adjusted dynamically based on current conditions. The current conditions in the data center may be a function of the nature of all the current workloads. Instead of simply managing the workloads in a way to increase overall execution efficiency, the data center instead may manage the workload to achieve quality of service requirements for particular workloads according to service level agreements.

公开(公告)号：US20180004452A1

公开(公告)日：2018-01-04

申请号：US15197948

申请日：2016-06-30

Applicant: Intel Corporation

Inventor： Mrittika Ganguli ,  Ananth S. Narayan ,  Anjaneya R. Chagam Reddy ,  Mohan J. Kumar

IPC: G06F3/06

CPC classification number: G06F3/0653 ,  G06F3/0604 ,  G06F3/0605 ,  G06F3/061 ,  G06F3/0629 ,  G06F3/067

Abstract: Technologies for providing dynamically managed quality of service in a distributed storage system include an apparatus having a processor. The processor is to determine capabilities of one or more compute devices of the distributed storage system. The processor is also to obtain an indicator of a target quality of service to be provided by the distributed storage system, determine target performance metrics associated with the target quality of service, determine target configuration settings for the one or more compute devices of the distributed storage system to provide the target quality of service, configure the one or more compute devices with the target configuration settings, determine whether a present performance of the distributed storage system satisfies the target quality of service, and reconfigure the one or more compute devices in response to a determination that the target quality of service is not satisfied. Other embodiments are described and claimed.

公开(公告)号：US12155538B2

公开(公告)日：2024-11-26

申请号：US18210478

申请日：2023-06-15

Applicant: Intel Corporation

Inventor： Mrittika Ganguli ,  Muthuvel M. I ,  Ananth S. Narayan ,  Jaideep Moses ,  Andrew J. Herdrich ,  Rahul Khanna

IPC: H04L41/50 ,  H04L41/14 ,  H04L41/5009 ,  H04L41/5025

Abstract: In accordance with some embodiments, a cloud service provider may operate a data center in a way that dynamically reallocates resources across nodes within the data center based on both utilization and service level agreements. In other words, the allocation of resources may be adjusted dynamically based on current conditions. The current conditions in the data center may be a function of the nature of all the current workloads. Instead of simply managing the workloads in a way to increase overall execution efficiency, the data center instead may manage the workload to achieve quality of service requirements for particular workloads according to service level agreements.

公开(公告)号：US11689471B2

公开(公告)日：2023-06-27

申请号：US17562664

申请日：2021-12-27

Applicant: Intel Corporation

Inventor： Subramony Sesha ,  Archana Patni ,  Ananth S. Narayan ,  Mrittika Ganguli

IPC: G06F15/173 ,  H04L47/70 ,  G06F9/50 ,  H04L67/568 ,  H04L67/1095 ,  G06F9/455 ,  H04L43/16 ,  H04L67/1097

CPC classification number: H04L47/70 ,  G06F9/45504 ,  G06F9/505 ,  G06F9/5027 ,  H04L43/16 ,  H04L67/1095 ,  H04L67/1097 ,  H04L67/568

Abstract: Technologies for contention-aware cloud compute scheduling include a number of compute nodes in a cloud computing cluster and a cloud controller. Each compute node collects performance data indicative of cache contention on the compute node, for example, cache misses per thousand instructions. Each compute node determines a contention score as a function of the performance data and stores the contention score in a cloud state database. In response to a request for a new virtual machine, the cloud controller receives contention scores for the compute nodes and selects a compute node based on the contention score. The cloud controller schedules the new virtual machine on the selected compute node. The contention score may include a contention metric and a contention score level indicative of the contention metric. The contention score level may be determined by comparing the contention metric to a number of thresholds. Other embodiments are described and claimed.

公开(公告)号：US10554505B2

公开(公告)日：2020-02-04

申请号：US13630545

申请日：2012-09-28

Applicant: Intel Corporation

Inventor： Mrittika Ganguli ,  Muthuvel M. I ,  Ananth S. Narayan ,  Jaideep Moses ,  Andrew J. Herdrich ,  Rahul Khanna

IPC: H04L12/24

Abstract: In accordance with some embodiments, a cloud service provider may operate a data center in a way that dynamically reallocates resources across nodes within the data center based on both utilization and service level agreements. In other words, the allocation of resources may be adjusted dynamically based on current conditions. The current conditions in the data center may be a function of the nature of all the current workloads. Instead of simply managing the workloads in a way to increase overall execution efficiency, the data center instead may manage the workload to achieve quality of service requirements for particular workloads according to service level agreements.

公开(公告)号：US09871742B2

公开(公告)日：2018-01-16

申请号：US15388843

申请日：2016-12-22

Applicant: Intel Corporation

Inventor： Subramony Sesha ,  Archana Patni ,  Ananth S. Narayan ,  Mrittika Ganguli

IPC: G06F15/173 ,  H04L12/911 ,  H04L29/08 ,  H04L12/26 ,  G06F9/50 ,  G06F9/455

CPC classification number: H04L47/70 ,  G06F9/45504 ,  G06F9/5027 ,  G06F9/505 ,  H04L43/16 ,  H04L67/1095 ,  H04L67/1097 ,  H04L67/2842

Abstract: Technologies for contention-aware cloud compute scheduling include a number of compute nodes in a cloud computing cluster and a cloud controller. Each compute node collects performance data indicative of cache contention on the compute node, for example, cache misses per thousand instructions. Each compute node determines a contention score as a function of the performance data and stores the contention score in a cloud state database. In response to a request for a new virtual machine, the cloud controller receives contention scores for the compute nodes and selects a compute node based on the contention score. The cloud controller schedules the new virtual machine on the selected compute node. The contention score may include a contention metric and a contention score level indicative of the contention metric. The contention score level may be determined by comparing the contention metric to a number of thresholds. Other embodiments are described and claimed.