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公开(公告)号：US20240428570A1
公开(公告)日：2024-12-26
申请号：US18824483
申请日：2024-09-04
Applicant: Cisco Technology, Inc.
Inventor： Elvira Dzhuraeva , Xinyuan Huang , Ashutosh Arwind Malegaonkar , Patrick James Riel
IPC: G06V10/774 , G06V10/776 , G06V10/82
Abstract: Systems, methods, and computer-readable media are disclosed for dynamically adjusting a configuration of a pre-processor and/or a post-processor of a machine learning system. In one aspect, a machine learning system can receive raw data at a pre-processor where the pre-processor being configured to generate pre-processed data, train a machine learning model based on the pre-processed data to generate output data, process the output data at a post-processor to generate inference data, and adjust, by a controller, configuration of one or a combination of the pre-processor and the post-processor based on the inference data.
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公开(公告)号：US11847500B2
公开(公告)日：2023-12-19
申请号：US16710499
申请日：2019-12-11
Applicant: Cisco Technology, Inc.
Inventor： Johnu George , Sourav Chakraborty , Amit Kumar Saha , Debojyoti Dutta , Xinyuan Huang , Adhita Selvaraj
IPC: G06F9/50 , G06N20/00 , G06F9/48 , G06F9/38 , G06F18/23213
CPC classification number: G06F9/5044 , G06F9/3836 , G06F9/48 , G06F9/4806 , G06F9/4843 , G06F9/4881 , G06F9/50 , G06F9/5005 , G06F9/5011 , G06F9/5022 , G06F9/5027 , G06F9/5038 , G06F9/5055 , G06F9/5061 , G06F9/5077 , G06F18/23213 , G06N20/00
Abstract: A method can include receiving, at a workflow controller, a machine learning workflow, the machine learning workflow associated with a first task and a second task. The first task is training a machine learning model and the second task is deploying the model. The method can include segmenting, by the workflow controller, the machine learning workflow into a first sub-workflow associated with the first task and a second sub-workflow associated with the second task, assigning a first workflow agent to the first sub-workflow and assigning a second workflow agent to the second sub-workflow, selecting, by the first workflow agent and based on first resources needed to perform the first task, a first cluster for performing the first task and selecting, by the second workflow agent and based on second resources needed to perform the second task, a second cluster for performing the second task.
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公开(公告)号：US20230393896A1
公开(公告)日：2023-12-07
申请号：US17830716
申请日：2022-06-02
Applicant: Cisco Technology, Inc.
Inventor： Ashutosh Arwind Malegaonkar , Patrick James Riel , Xinyuan Huang , Elvira Dzhuraeva
CPC classification number: G06F9/5038 , G06N20/00
Abstract: Systems, methods, and computer-readable media are disclosed for a dynamic and intelligent machine learning scheduling platform for running multiple machine learning models simultaneously. The present technology includes receiving output data of a first machine learning model running on an edge device. Further, the present technology includes accessing a set of dynamic rules for scheduling a second machine learning model to run on the edge device. As follows, the present technology includes determining to run the second machine learning model on the edge device in accordance with the set of rules where the first machine learning model and the second machine learning model are run on the edge device in parallel.
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公开(公告)号：US10769152B2
公开(公告)日：2020-09-08
申请号：US15368373
申请日：2016-12-02
Applicant: CISCO TECHNOLOGY, INC.
Inventor： Xinyuan Huang , Manoj Sharma , Debojyoti Dutta
IPC: G06F16/22 , G06F16/2455
Abstract: There is disclosed in an example a computer-implemented method of providing automated log analysis, including: receiving a log stream comprising a plurality of transaction log entries, the log entries comprising a time stamp, a component identification (ID), and a name value pair identifying a transaction; creating an index comprising mapping a key ID to a name value pair of a log entry; and selecting from the index a key ID having a relatively large number of repetitions. There is also disclosed an apparatus and computer-readable medium for performing the method.
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公开(公告)号：US20190303018A1
公开(公告)日：2019-10-03
申请号：US15943640
申请日：2018-04-02
Applicant: Cisco Technology, Inc.
Inventor： Xinyuan Huang , Johnu George , Marc Solanas Tarre , Komei Shimamura , Purushotham Kamath , Debojyoti Dutta
Abstract: Aspects of the technology provide improvements to a Serverless Computing (SLC) workflow by determining when and how to optimize SLC jobs for computing in a Distributed Computing Framework (DCF). DCF optimization can be performed by abstracting SLC tasks into different workflow configurations to determined optimal arrangements for execution in a DCF environment. A process of the technology can include steps for receiving an SLC job including one or more SLC tasks, executing one or more of the tasks to determine a latency metric and a throughput metric for the SLC tasks, and determining if the SLC tasks should be converted to a Distributed Computing Framework (DCF) format based on the latency metric and the throughput metric. Systems and machine-readable media are also provided.
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Patent Agency Ranking
公开(公告)号：US20190149440A1
公开(公告)日：2019-05-16
申请号：US15810552
申请日：2017-11-13
Applicant: Cisco Technology, Inc.
Inventor： Ralf Rantzau , Xinyuan Huang , Purushotham Kamath , Debojyoti Dutta
Abstract: In one embodiment, a service converts a stream of network telemetry data into sketches. The stream of network telemetry data comprises a plurality of characteristics of traffic observed in a network. The service forms a time series of the sketches. The service performs anomaly detection on the time series of the sketches in part by calculating a joint distribution of ranks and frequencies of a portion of the characteristics at different points in time of the time series. The service sends an anomaly detection alert, when an anomaly is detected from the time series of the sketches.
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公开(公告)号：US20190026150A1
公开(公告)日：2019-01-24
申请号：US15655648
申请日：2017-07-20
Applicant: CISCO TECHNOLOGY, INC.
Inventor： Komei Shimamura , Xinyuan Huang , Amit Kumar Saha , Debojyoti Dutta
Abstract: In one embodiment, a method for FPGA accelerated serverless computing comprises receiving, from a user, a definition of a serverless computing task comprising one or more functions to be executed. A task scheduler performs an initial placement of the serverless computing task to a first host determined to be a first optimal host for executing the serverless computing task. The task scheduler determines a supplemental placement of a first function to a second host determined to be a second optimal host for accelerating execution of the first function, wherein the first function is not able to accelerated by one or more FPGAs in the first host. The serverless computing task is executed on the first host and the second host according to the initial placement and the supplemental placement.
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公开(公告)号：US11119821B2
公开(公告)日：2021-09-14
申请号：US16693930
申请日：2019-11-25
Applicant: Cisco Technology, Inc.
Inventor： Komei Shimamura , Xinyuan Huang , Amit Kumar Saha , Debojyoti Dutta
Abstract: In one embodiment, a method for FPGA accelerated serverless computing comprises receiving, from a user, a definition of a serverless computing task comprising one or more functions to be executed. A task scheduler performs an initial placement of the serverless computing task to a first host determined to be a first optimal host for executing the serverless computing task. The task scheduler determines a supplemental placement of a first function to a second host determined to be a second optimal host for accelerating execution of the first function, wherein the first function is not able to accelerated by one or more FPGAs in the first host. The serverless computing task is executed on the first host and the second host according to the initial placement and the supplemental placement.
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公开(公告)号：US20210182729A1
公开(公告)日：2021-06-17
申请号：US16710499
申请日：2019-12-11
Applicant: Cisco Technology, Inc.
Inventor： Johnu George , Sourav Chakraborty , Amit Kumar Saha , Debojyoti Dutta , Xinyuan Huang , Adhita Selvaraj
Abstract: A method can include receiving, at a workflow controller, a machine learning workflow, the machine learning workflow associated with a first task and a second task. The first task is training a machine learning model and the second task is deploying the model. The method can include segmenting, by the workflow controller, the machine learning workflow into a first sub-workflow associated with the first task and a second sub-workflow associated with the second task, assigning a first workflow agent to the first sub-workflow and assigning a second workflow agent to the second sub-workflow, selecting, by the first workflow agent and based on first resources needed to perform the first task, a first cluster for performing the first task and selecting, by the second workflow agent and based on second resources needed to perform the second task, a second cluster for performing the second task.
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公开(公告)号：US20200089532A1
公开(公告)日：2020-03-19
申请号：US16693930
申请日：2019-11-25
Applicant: Cisco Technology, Inc.
Inventor： Komei Shimamura , Xinyuan Huang , Amit Kumar Saha , Debojyoti Dutta
Abstract: In one embodiment, a method for FPGA accelerated serverless computing comprises receiving, from a user, a definition of a serverless computing task comprising one or more functions to be executed. A task scheduler performs an initial placement of the serverless computing task to a first host determined to be a first optimal host for executing the serverless computing task. The task scheduler determines a supplemental placement of a first function to a second host determined to be a second optimal host for accelerating execution of the first function, wherein the first function is not able to accelerated by one or more FPGAs in the first host. The serverless computing task is executed on the first host and the second host according to the initial placement and the supplemental placement.
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