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公开(公告)号:US20210303137A1
公开(公告)日:2021-09-30
申请号:US17315672
申请日:2021-05-10
Applicant: Intel Corporation
Inventor: Fatema Adenwala , Ankitha Chandran , Nageen Himayat , Florence Pon , Divya Vijayaraghavan
IPC: G06F3/0484 , G07C5/00 , H04W4/21 , H04W4/46 , G06F3/0481 , H04W4/44 , H04W4/02
Abstract: Apparatuses, methods and storage medium associated with computer-assisted or autonomous driving (CA/AD) vehicles are disclosed herein. In embodiments, CA/AD vehicles are members of a CA/AD vehicle social network (CASN) in which various CA/AD vehicles may form connections or relationships with one another. CA/AD vehicles that have an existing relationship or connection may share CASN information with one another. The CASN information may include authenticated and/or proprietary information. Other embodiments are also described and claimed.
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2.
公开(公告)号:US20190050715A1
公开(公告)日:2019-02-14
申请号:US16147037
申请日:2018-09-28
Applicant: Intel Corporation
Inventor: Kooi Chi Ooi , Min Suet Lim , Denica Larsen , Lady Nataly Pinilla Pico , Divya Vijayaraghavan
Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to improve data training of a machine learning model using a field-programmable gate array (FPGA). An example system includes one or more computation modules, each of the one or more computation modules associated with a corresponding user, the one or more computation modules training first neural networks using data associated with the corresponding users, and FPGA to obtain a first set of parameters from each of the one or more computation modules, the first set of parameters associated with the first neural networks, configure a second neural network based on the first set of parameters, execute the second neural network to generate a second set of parameters, and transmit the second set of parameters to the first neural networks to update the first neural networks.
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公开(公告)号:US11036370B2
公开(公告)日:2021-06-15
申请号:US16141219
申请日:2018-09-25
Applicant: Intel Corporation
Inventor: Fatema Adenwala , Ankitha Chandran , Nageen Himayat , Florence Pon , Divya Vijayaraghavan
IPC: H04W4/44 , G06F3/0484 , G07C5/00 , H04W4/21 , H04W4/46 , G06F3/0481 , H04W4/02 , G05D1/00 , G05D1/02
Abstract: Apparatuses, methods and storage medium associated with computer-assisted or autonomous driving (CA/AD) vehicles are disclosed herein. In embodiments, CA/AD vehicles are members of a CA/AD vehicle social network (CASN) in which various CA/AD vehicles may form connections or relationships with one another. CA/AD vehicles that have an existing relationship or connection may share CASN information with one another. The CASN information may include authenticated and/or proprietary information. Other embodiments are also described and claimed.
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公开(公告)号:US11030012B2
公开(公告)日:2021-06-08
申请号:US16146845
申请日:2018-09-28
Applicant: Intel Corporation
Inventor: Divya Vijayaraghavan , Denica Larsen , Kooi Chi Ooi , Lady Nataly Pinilla Pico , Min Suet Lim
Abstract: Methods, apparatus, systems, and articles of manufacture for allocating a workload to an accelerator using machine learning are disclosed. An example apparatus includes a workload attribute determiner to identify a first attribute of a first workload and a second attribute of a second workload. An accelerator selection processor causes at least a portion of the first workload to be executed by at least two accelerators, accesses respective performance metrics corresponding to execution of the first workload by the at least two accelerators, and selects a first accelerator of the at least two accelerators based on the performance metrics. A neural network trainer trains a machine learning model based on an association between the first accelerator and the first attribute of the first workload. A neural network processor processes, using the machine learning model, the second attribute to select one of the at least two accelerators to execute the second workload.
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公开(公告)号:US11586473B2
公开(公告)日:2023-02-21
申请号:US17317679
申请日:2021-05-11
Applicant: Intel Corporation
Inventor: Divya Vijayaraghavan , Denica Larsen , Kooi Chi Ooi , Lady Nataly Pinilla Pico , Min Suet Lim
Abstract: Methods, apparatus, systems, and articles of manufacture for allocating a workload to an accelerator using machine learning are disclosed. An example apparatus includes a workload attribute determiner to identify a first attribute of a first workload and a second attribute of a second workload. An accelerator selection processor causes at least a portion of the first workload to be executed by at least two accelerators, accesses respective performance metrics corresponding to execution of the first workload by the at least two accelerators, and selects a first accelerator of the at least two accelerators based on the performance metrics. A neural network trainer trains a machine learning model based on an association between the first accelerator and the first attribute of the first workload. A neural network processor processes, using the machine learning model, the second attribute to select one of the at least two accelerators to execute the second workload.
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公开(公告)号:US11710029B2
公开(公告)日:2023-07-25
申请号:US16147037
申请日:2018-09-28
Applicant: Intel Corporation
Inventor: Kooi Chi Ooi , Min Suet Lim , Denica Larsen , Lady Nataly Pinilla Pico , Divya Vijayaraghavan
IPC: G06N3/045 , G06N3/08 , G06N5/04 , G06N3/063 , G06F15/78 , G06F1/16 , G06N20/00 , G06F16/00 , G06N3/084 , G06V10/94 , G06F18/214 , G06F18/21 , G06F18/2413 , G06N3/048 , G06V10/764 , G06V10/774 , G06V10/776 , G06V10/82
CPC classification number: G06N3/063 , G06F1/163 , G06F15/7892 , G06F16/00 , G06F18/214 , G06F18/217 , G06F18/24143 , G06N3/045 , G06N3/048 , G06N3/08 , G06N3/084 , G06N5/04 , G06N20/00 , G06V10/764 , G06V10/774 , G06V10/776 , G06V10/82 , G06V10/955
Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to improve data training of a machine learning model using a field-programmable gate array (FPGA). An example system includes one or more computation modules, each of the one or more computation modules associated with a corresponding user, the one or more computation modules training first neural networks using data associated with the corresponding users, and FPGA to obtain a first set of parameters from each of the one or more computation modules, the first set of parameters associated with the first neural networks, configure a second neural network based on the first set of parameters, execute the second neural network to generate a second set of parameters, and transmit the second set of parameters to the first neural networks to update the first neural networks.
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公开(公告)号:US20210406085A1
公开(公告)日:2021-12-30
申请号:US17317679
申请日:2021-05-11
Applicant: Intel Corporation
Inventor: Divya Vijayaraghavan , Denica Larsen , Kooi Chi Ooi , Lady Nataly Pinilla Pico , Min Suet Lim
Abstract: Methods, apparatus, systems, and articles of manufacture for allocating a workload to an accelerator using machine learning are disclosed. An example apparatus includes a workload attribute determiner to identify a first attribute of a first workload and a second attribute of a second workload. An accelerator selection processor causes at least a portion of the first workload to be executed by at least two accelerators, accesses respective performance metrics corresponding to execution of the first workload by the at least two accelerators, and selects a first accelerator of the at least two accelerators based on the performance metrics. A neural network trainer trains a machine learning model based on an association between the first accelerator and the first attribute of the first workload. A neural network processor processes, using the machine learning model, the second attribute to select one of the at least two accelerators to execute the second workload.
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公开(公告)号:US20190079659A1
公开(公告)日:2019-03-14
申请号:US16141219
申请日:2018-09-25
Applicant: Intel Corporation
Inventor: Fatema Adenwala , Ankitha Chandran , Nageen Himayat , Florence Pon , Divya Vijayaraghavan
IPC: G06F3/0484 , G07C5/00 , H04W4/21 , H04W4/46 , H04W4/44 , G06F3/0481
Abstract: Apparatuses, methods and storage medium associated with computer-assisted or autonomous driving (CA/AD) vehicles are disclosed herein. In embodiments, CA/AD vehicles are members of a CA/AD vehicle social network (CASN) in which various CA/AD vehicles may form connections or relationships with one another. CA/AD vehicles that have an existing relationship or connection may share CASN information with one another. The CASN information may include authenticated and/or proprietary information. Other embodiments are also described and claimed.
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公开(公告)号:US20230359336A1
公开(公告)日:2023-11-09
申请号:US18352224
申请日:2023-07-13
Applicant: Intel Corporation
Inventor: Fatema Adenwala , Ankitha Chandran , Nageen Himayat , Florence Pon , Divya Vijayaraghavan
IPC: G07C5/00 , H04W4/02 , H04W4/21 , H04W4/46 , G06F3/04842 , G06F3/0481 , H04W4/44
CPC classification number: G06F3/04842 , G06F3/0481 , G07C5/008 , H04W4/026 , H04W4/21 , H04W4/44 , H04W4/46 , G05D1/0088 , G05D2201/0213
Abstract: Apparatuses, methods and storage medium associated with computer-assisted or autonomous driving (CA/AD) vehicles are disclosed herein. In embodiments, CA/AD vehicles are members of a CA/AD vehicle social network (CASN) in which various CA/AD vehicles may form connections or relationships with one another. CA/AD vehicles that have an existing relationship or connection may share CASN information with one another. The CASN information may include authenticated and/or proprietary information. Other embodiments are also described and claimed.
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公开(公告)号:US11704007B2
公开(公告)日:2023-07-18
申请号:US17315672
申请日:2021-05-10
Applicant: Intel Corporation
Inventor: Fatema Adenwala , Ankitha Chandran , Nageen Himayat , Florence Pon , Divya Vijayaraghavan
IPC: H04W4/46 , H04W4/44 , G06F3/04842 , G07C5/00 , H04W4/21 , G06F3/0481 , H04W4/02 , G05D1/00 , G05D1/02
CPC classification number: G06F3/04842 , G06F3/0481 , G07C5/008 , H04W4/026 , H04W4/21 , H04W4/44 , H04W4/46 , G05D1/0088 , G05D1/0287 , G05D2201/0213
Abstract: Apparatuses, methods and storage medium associated with computer-assisted or autonomous driving (CA/AD) vehicles are disclosed herein. In embodiments, CA/AD vehicles are members of a CA/AD vehicle social network (CASN) in which various CA/AD vehicles may form connections or relationships with one another. CA/AD vehicles that have an existing relationship or connection may share CASN information with one another. The CASN information may include authenticated and/or proprietary information. Other embodiments are also described and claimed.
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