公开(公告)号：US11082525B2

公开(公告)日：2021-08-03

申请号：US16415138

申请日：2019-05-17

Applicant: Intel Corporation

Inventor： Ramanathan Sethuraman ,  Timothy Verrall ,  Ned M. Smith ,  Thomas Willhalm ,  Brinda Ganesh ,  Francesc Guim Bernat ,  Karthik Kumar ,  Evan Custodio ,  Suraj Prabhakaran ,  Ignacio Astilleros Diez ,  Nilesh K. Jain ,  Ravi Iyer ,  Andrew J. Herdrich ,  Alexander Vul ,  Patrick G. Kutch ,  Kevin Bohan ,  Trevor Cooper

IPC: H04L29/08 ,  H04L29/06 ,  H04L9/08

Abstract: Technologies for managing telemetry and sensor data on an edge networking platform are disclosed. According to one embodiment disclosed herein, a device monitors telemetry data associated with multiple services provided in the edge networking platform. The device identifies, for each of the services and as a function of the associated telemetry data, one or more service telemetry patterns. The device generates a profile including the identified service telemetry patterns.

公开(公告)号：US20190340539A1

公开(公告)日：2019-11-07

申请号：US16513800

申请日：2019-07-17

Applicant: Intel Corporation

Inventor： Luis S. Kida ,  Nilesh K. Jain ,  Darshan Iyer ,  Ebrahim Al Safadi

IPC: G06N20/00

Abstract: Technologies for platform-targeted machine learning include a computing device to generate a machine learning algorithm model indicative of a plurality of classes between which a user input is to be classified and translate the machine learning algorithm model into hardware code for execution on the target platform. The user input is to be classified as being associated with a particular class based on an application of one or more features to the user input, and each of the one or more features has an associated implementation cost indicative of a cost to perform on a target platform on which the corresponding feature is to be applied to the user input.

公开(公告)号：US20220166846A1

公开(公告)日：2022-05-26

申请号：US17390658

申请日：2021-07-30

Applicant: Intel Corporation

Inventor： Ramanathan Sethuraman ,  Timothy Verrall ,  Ned M. Smith ,  Thomas Willhalm ,  Brinda Ganesh ,  Francesc Guim Bernat ,  Karthik Kumar ,  Evan Custodio ,  Suraj Prabhakaran ,  Ignacio Astilleros Diez ,  Nilesh K. Jain ,  Ravi Iyer ,  Andrew J. Herdrich ,  Alexander Vul ,  Patrick G. Kutch ,  Kevin Bohan ,  Trevor Cooper

IPC: H04L67/303 ,  H04L9/40 ,  H04L9/08 ,  H04L67/12

Abstract: Technologies for managing telemetry and sensor data on an edge networking platform are disclosed. According to one embodiment disclosed herein, a device monitors telemetry data associated with multiple services provided in the edge networking platform. The device identifies, for each of the services and as a function of the associated telemetry data, one or more service telemetry patterns. The device generates a profile including the identified service telemetry patterns.

公开(公告)号：US20190281132A1

公开(公告)日：2019-09-12

申请号：US16415138

申请日：2019-05-17

Applicant: Intel Corporation

Inventor： Ramanathan Sethuraman ,  Timothy Verrall ,  Ned M. Smith ,  Thomas Willhalm ,  Brinda Ganesh ,  Francesc Guim Bernat ,  Karthik Kumar ,  Evan Custodio ,  Suraj Prabhakaran ,  Ignacio Astilleros Diez ,  Nilesh K. Jain ,  Ravi Iyer ,  Andrew J. Herdrich ,  Alexander Vul ,  Patrick G. Kutch ,  Kevin Bohan ,  Trevor Cooper

IPC: H04L29/08 ,  H04L9/08 ,  H04L29/06

Abstract: Technologies for managing telemetry and sensor data on an edge networking platform are disclosed. According to one embodiment disclosed herein, a device monitors telemetry data associated with multiple services provided in the edge networking platform. The device identifies, for each of the services and as a function of the associated telemetry data, one or more service telemetry patterns. The device generates a profile including the identified service telemetry patterns.

公开(公告)号：US20190050688A1

公开(公告)日：2019-02-14

申请号：US15673069

申请日：2017-08-09

Applicant: Intel Corporation

Inventor： Darshan Iyer ,  Nilesh K. Jain

IPC: G06K9/62

Abstract: Methods, apparatus, systems and articles of manufacture to analyze time series data are disclosed. An example method includes sub sampling time series data collected by a sensor to generate one or more candidate samples of interest within the time series data. Feature vectors are generated for respective ones of the one or more candidate samples of interest. Classification of the feature vectors is attempted based on a model. In response to a classification of one of the feature vectors, the classification is stored in connection with the corresponding candidate sample.

公开(公告)号：US11922220B2

公开(公告)日：2024-03-05

申请号：US17255588

申请日：2019-04-16

Applicant: Intel Corporation

Inventor： Mohammad R. Haghighat ,  Kshitij Doshi ,  Andrew J. Herdrich ,  Anup Mohan ,  Ravishankar R. Iyer ,  Mingqiu Sun ,  Krishna Bhuyan ,  Teck Joo Goh ,  Mohan J. Kumar ,  Michael Prinke ,  Michael Lemay ,  Leeor Peled ,  Jr-Shian Tsai ,  David M. Durham ,  Jeffrey D. Chamberlain ,  Vadim A. Sukhomlinov ,  Eric J. Dahlen ,  Sara Baghsorkhi ,  Harshad Sane ,  Areg Melik-Adamyan ,  Ravi Sahita ,  Dmitry Yurievich Babokin ,  Ian M. Steiner ,  Alexander Bachmutsky ,  Anil Rao ,  Mingwei Zhang ,  Nilesh K. Jain ,  Amin Firoozshahian ,  Baiju V. Patel ,  Wenyong Huang ,  Yeluri Raghuram

IPC: G06F9/50 ,  G06F9/52 ,  G06F11/30 ,  G06F11/34 ,  G06F21/53 ,  G06F21/56 ,  G06F21/60 ,  G06N20/00

CPC classification number: G06F9/5061 ,  G06F9/52 ,  G06F11/302 ,  G06F11/3495 ,  G06F21/53 ,  G06F21/604 ,  G06F21/56 ,  G06F2209/521 ,  G06F2221/033 ,  G06N20/00

Abstract: Embodiments of systems, apparatuses and methods provide enhanced function as a service (FaaS) to users, e.g., computer developers and cloud service providers (CSPs). A computing system configured to provide such enhanced FaaS service include one or more controls architectural subsystems, software and orchestration subsystems, network and storage subsystems, and security subsystems. The computing system executes functions in response to events triggered by the users in an execution environment provided by the architectural subsystems, which represent an abstraction of execution management and shield the users from the burden of managing the execution. The software and orchestration subsystems allocate computing resources for the function execution by intelligently spinning up and down containers for function code with decreased instantiation latency and increased execution scalability while maintaining secured execution. Furthermore, the computing system enables customers to pay only when their code gets executed with a granular billing down to millisecond increments.

公开(公告)号：US20220108224A1

公开(公告)日：2022-04-07

申请号：US17554975

申请日：2021-12-17

Applicant: Intel Corporation

Inventor： Luis S. Kida ,  Nilesh K. Jain ,  Darshan Iyer ,  Ebrahim Al Safadi

IPC: G06N20/00

Abstract: Technologies for platform-targeted machine learning include a computing device to generate a machine learning algorithm model indicative of a plurality of classes between which a user input is to be classified and translate the machine learning algorithm model into hardware code for execution on the target platform. Example instructions cause a processor to obtain dataset features indicative of a plurality of characteristics of an input dataset, rank, using multiple ranking algorithms, the dataset features, identify feature subsets for respective ones of the ranked dataset features, predict performance metrics based on the feature subsets, and select a final subset based on the predicted performance metrics.

公开(公告)号：US20210263779A1

公开(公告)日：2021-08-26

申请号：US17255588

申请日：2019-04-16

Applicant: Intel Corporation

Inventor： Mohammad R. Haghighat ,  Kshitij Doshi ,  Andrew J. Herdrich ,  Anup Mohan ,  Ravishankar R. Iyer ,  Mingqiu Sun ,  Krishna Bhuyan ,  Teck Joo Goh ,  Mohan J. Kumar ,  Michael Prinke ,  Michael Lemay ,  Leeor Peled ,  Jr-Shian Tsai ,  David M. Durham ,  Jeffrey D. Chamberlain ,  Vadim A. Sukhomlinov ,  Eric J. Dahlen ,  Sara Baghsorkhi ,  Harshad Sane ,  Areg Melik-Adamyan ,  Ravi Sahita ,  Dmitry Yurievich Babokin ,  Ian M. Steiner ,  Alexander Bachmutsky ,  Anil Rao ,  Mingwei Zhang ,  Nilesh K. Jain ,  Amin Firoozshahian ,  Baiju V. Patel ,  Wenyong Huang ,  Yeluri Raghuram

IPC: G06F9/50 ,  G06F21/53 ,  G06F9/52 ,  G06F21/60 ,  G06F11/30 ,  G06F11/34

Abstract: Embodiments of systems, apparatuses and methods provide enhanced function as a service (FaaS) to users, e.g., computer developers and cloud service providers (CSPs). A computing system configured to provide such enhanced FaaS service include one or more controls architectural subsystems, software and orchestration subsystems, network and storage subsystems, and security subsystems. The computing system executes functions in response to events triggered by the users in an execution environment provided by the architectural subsystems, which represent an abstraction of execution management and shield the users from the burden of managing the execution. The software and orchestration subsystems allocate computing resources for the function execution by intelligently spinning up and down containers for function code with decreased instantiation latency and increased execution scalability while maintaining secured execution. Furthermore, the computing system enables customers to pay only when their code gets executed with a granular billing down to millisecond increments.

公开(公告)号：US10956792B2

公开(公告)日：2021-03-23

申请号：US15673069

申请日：2017-08-09

Applicant: Intel Corporation

Inventor： Darshan Iyer ,  Nilesh K. Jain

IPC: G06K9/62 ,  G06K9/00 ,  A61B5/0452 ,  A61B5/00 ,  G06N3/08 ,  G06N3/02

Abstract: Methods, apparatus, systems and articles of manufacture to analyze time series data are disclosed. An example method includes sub sampling time series data collected by a sensor to generate one or more candidate samples of interest within the time series data. Feature vectors are generated for respective ones of the one or more candidate samples of interest. Classification of the feature vectors is attempted based on a model. In response to a classification of one of the feature vectors, the classification is stored in connection with the corresponding candidate sample.

公开(公告)号：US10373069B2

公开(公告)日：2019-08-06

申请号：US14866895

申请日：2015-09-26

Applicant: Intel Corporation

Inventor： Luis S. Kida ,  Nilesh K. Jain ,  Darshan Iyer ,  Ebrahim Al Safadi

IPC: G06N20/00

Abstract: Technologies for platform-targeted machine learning include a computing device to generate a machine learning algorithm model indicative of a plurality of classes between which a user input is to be classified and translate the machine learning algorithm model into hardware code for execution on the target platform. The user input is to be classified as being associated with a particular class based on an application of one or more features to the user input, and each of the one or more features has an associated implementation cost indicative of a cost to perform on a target platform on which the corresponding feature is to be applied to the user input.