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公开(公告)号：US11815992B2
公开(公告)日：2023-11-14
申请号：US17494473
申请日：2021-10-05
Applicant: Intel Corporation
Inventor： Jerin C. Justin , Kumar Balasubramanian , Naveen Manicka
CPC classification number: G06F11/0793 , G06F11/0709 , G06F11/079 , G06F11/0751 , G06F11/0787
Abstract: A computing device and method for profiling and diagnostics in an Internet of Things (IoT) system, including matching an observed solution characteristic of the IoT system to an anomaly in an anomaly database.
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公开(公告)号：US20220197734A1
公开(公告)日：2022-06-23
申请号：US17494473
申请日：2021-10-05
Applicant: Intel Corporation
Inventor： Jerin C. Justin , Kumar Balasubramanian , Naveen Manicka
IPC: G06F11/07
Abstract: A computing device and method for profiling and diagnostics in an Internet of Things (IoT) system, including matching an observed solution characteristic of the IoT system to an anomaly in an anomaly database.
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公开(公告)号：US10546393B2
公开(公告)日：2020-01-28
申请号：US15859408
申请日：2017-12-30
Applicant: Intel Corporation
Inventor： Joydeep Ray , Ben Ashbaugh , Prasoonkumar Surti , Pradeep Ramani , Rama Harihara , Jerin C. Justin , Jing Huang , Xiaoming Cui , Timothy B. Costa , Ting Gong , Elmoustapha Ould-Ahmed-Vall , Kumar Balasubramanian , Anil Thomas , Oguz H. Elibol , Jayaram Bobba , Guozhong Zhuang , Bhavani Subramanian , Gokce Keskin , Chandrasekaran Sakthivel , Rajesh Poornachandran
Abstract: Embodiments are generally directed to compression in machine learning and deep learning processing. An embodiment of an apparatus for compression of untyped data includes a graphical processing unit (GPU) including a data compression pipeline, the data compression pipeline including a data port coupled with one or more shader cores, wherein the data port is to allow transfer of untyped data without format conversion, and a 3D compression/decompression unit to provide for compression of untyped data to be stored to a memory subsystem and decompression of untyped data from the memory subsystem.
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公开(公告)号：US20240070926A1
公开(公告)日：2024-02-29
申请号：US18466141
申请日：2023-09-13
Applicant: Intel Corporation
Inventor： Joydeep Ray , Ben Ashbaugh , Prasoonkumar Surti , Pradeep Ramani , Rama Harihara , Jerin C. Justin , Jing Huang , Xiaoming Cui , Timothy B. Costa , Ting Gong , Elmoustapha Ould-ahmed-vall , Kumar Balasubramanian , Anil Thomas , Oguz H. Elibol , Jayaram Bobba , Guozhong Zhuang , Bhavani Subramanian , Gokce Keskin , Chandrasekaran Sakthivel , Rajesh Poornachandran
CPC classification number: G06T9/002 , G06F12/023 , G06T15/005 , G06F2212/302 , G06F2212/401
Abstract: Embodiments are generally directed to compression in machine learning and deep learning processing. An embodiment of an apparatus for compression of untyped data includes a graphical processing unit (GPU) including a data compression pipeline, the data compression pipeline including a data port coupled with one or more shader cores, wherein the data port is to allow transfer of untyped data without format conversion, and a 3D compression/decompression unit to provide for compression of untyped data to be stored to a memory subsystem and decompression of untyped data from the memory subsystem.
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公开(公告)号：US20230230289A1
公开(公告)日：2023-07-20
申请号：US18152643
申请日：2023-01-10
Applicant: Intel Corporation
Inventor： Joydeep Ray , Ben Ashbaugh , Prasoonkumar Surti , Pradeep Ramani , Rama Harihara , Jerin C. Justin , Jing Huang , Xiaoming Cui , Timothy B. Costa , Ting Gong , Elmoustapha Ould-ahmed-vall , Kumar Balasubramanian , Anil Thomas , Oguz H. Elibol , Jayaram Bobba , Guozhong Zhuang , Bhavani Subramanian , Gokce Keskin , Chandrasekaran Sakthivel , Rajesh Poornachandran
CPC classification number: G06T9/002 , G06F12/023 , G06T15/005 , G06F2212/401 , G06F2212/302
Abstract: Embodiments are generally directed to compression in machine learning and deep learning processing. An embodiment of an apparatus for compression of untyped data includes a graphical processing unit (GPU) including a data compression pipeline, the data compression pipeline including a data port coupled with one or more shader cores, wherein the data port is to allow transfer of untyped data without format conversion, and a 3D compression/decompression unit to provide for compression of untyped data to be stored to a memory subsystem and decompression of untyped data from the memory subsystem.
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Patent Agency Ranking
公开(公告)号：US20180063250A1
公开(公告)日：2018-03-01
申请号：US15638942
申请日：2017-06-30
Applicant: INTEL CORPORATION
Inventor： Jerin C. Justin , Kumar Balasubramanian
CPC classification number: H04L67/125 , G06F11/261 , G06F11/3006 , G06F11/3058 , G06F11/3414 , G06F11/3457 , H04L67/025 , H04L67/12 , H04L67/42
Abstract: A system and method for representing events that occur in a real world deployment is described. A real-world workload including multiple events is identified. Multiple characteristics of the real-world workload are converted into multiple endpoint simulator workloads. Multiple gateway hardware characteristics are converted into a modeling elements for simulated Internet of things (IoT) networks. Further, a simulation is performed for each of the endpoint simulator workloads on each of the simulated IoT networks. Also, statistics are collected about the performance of the simulated IoT networks for the endpoint simulator workloads.
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公开(公告)号：US20180062959A1
公开(公告)日：2018-03-01
申请号：US15638761
申请日：2017-06-30
Applicant: INTEL CORPORATION
Inventor： Jerin C. Justin , Kumar Balasubramanian
CPC classification number: A61B5/01 , A61B5/0008 , A61B5/02055 , A61B5/024 , A61B5/681 , G16H50/30 , H04L41/5006 , H04L43/08 , H04L67/22 , H04W4/70
Abstract: A method and apparatus including a computing device to quantify a term of a service agreement in a context of a proposed solution, evaluate solution characteristics against a given gateway architecture, and compare the solution characteristics to desired service-agreement solution metrics. The solution characteristics include simulated observed characteristics.
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公开(公告)号：US20180060159A1
公开(公告)日：2018-03-01
申请号：US15638616
申请日：2017-06-30
Applicant: INTEL CORPORATION
Inventor： Jerin C. Justin , Kumar Balasubramanian , Naveen Manicka
IPC: G06F11/07
CPC classification number: G06F11/0793 , G06F11/0709 , G06F11/0751 , G06F11/0787 , G06F11/079
Abstract: A computing device and method for profiling and diagnostics in an Internet of Things (IoT) system, including matching an observed solution characteristic of the IoT system to an anomaly in an anomaly database.
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公开(公告)号：US20240048621A1
公开(公告)日：2024-02-08
申请号：US18487277
申请日：2023-10-16
Applicant: Intel Corporation
Inventor： Jerin C. Justin , Kumar Balasubramanian
IPC: H04L67/125 , G06F11/30 , G06F11/34 , H04L67/01 , G06F30/20 , G06F11/26 , H04L67/025
CPC classification number: H04L67/125 , G06F11/3006 , G06F11/3457 , G06F11/3058 , G06F11/3414 , H04L67/01 , G06F30/20 , G06F11/261 , H04L67/025 , H04L67/12
Abstract: A system and method for representing events that occur in a real world deployment is described. A real-world workload including multiple events is identified. Multiple characteristics of the real-world workload are converted into multiple endpoint simulator workloads. Multiple gateway hardware characteristics are converted into a modeling elements for simulated Internet of things (IoT) networks. Further, a simulation is performed for each of the endpoint simulator workloads on each of the simulated IoT networks. Also, statistics are collected about the performance of the simulated IoT networks for the endpoint simulator workloads.
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公开(公告)号：US20230110334A1
公开(公告)日：2023-04-13
申请号：US17887628
申请日：2022-08-15
Applicant: Intel Corporation
Inventor： Jerin C. Justin , Kumar Balasubramanian
IPC: H04L67/125 , G06F11/30 , G06F11/34 , H04L67/01 , G06F11/26 , H04L67/025
Abstract: A system and method for representing events that occur in a real world deployment is described. A real-world workload including multiple events is identified. Multiple characteristics of the real-world workload are converted into multiple endpoint simulator workloads. Multiple gateway hardware characteristics are converted into a modeling elements for simulated Internet of things (IoT) networks. Further, a simulation is performed for each of the endpoint simulator workloads on each of the simulated IoT networks. Also, statistics are collected about the performance of the simulated IoT networks for the endpoint simulator workloads.
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