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    User-assisted training data denoising for predictive systems
    2.
    发明授权
    User-assisted training data denoising for predictive systems 有权

    公开(公告)号：US11979311B2

    公开(公告)日：2024-05-07

    申请号：US17547718

    申请日：2021-12-10

    申请人： Cisco Technology, Inc.

    发明人： Jean-Philippe Vasseur ,  Vinay Kumar Kolar

    IPC分类号： H04L45/00 ,  H04L41/5025 ,  H04L43/0852 ,  H04L45/02

    CPC分类号： H04L45/08 ,  H04L41/5025 ,  H04L43/0852

    摘要： In one embodiment, a device receives, via a user interface, an indication of what is considered noise within a time series of a path performance metric. The device selects, based on the indication, a particular denoising filter to be applied to telemetry data obtained from one or more network paths regarding the path performance metric. The device forms model training data by applying the particular denoising filter to telemetry data obtained from one or more network paths regarding the path performance metric. The device trains, using the model training data, a prediction model to predict when a given network path will experience a failure condition.

    Massively parallel in-network compute
    4.
    发明授权
    Massively parallel in-network compute 有权

    公开(公告)号：US11888931B1

    公开(公告)日：2024-01-30

    申请号：US17742354

    申请日：2022-05-11

    申请人： Innovium, Inc.

    发明人： William Brad Matthews ,  Puneet Agarwal ,  Bruce Hui Kwan

    IPC分类号： H04L67/1074 ,  H04L49/15 ,  G06N20/00 ,  G06N3/045 ,  H04L45/02

    CPC分类号： H04L67/1076 ,  G06N3/045 ,  G06N20/00 ,  H04L49/15 ,  H04L45/08

    摘要： Efficient scaling of in-network compute operations to large numbers of compute nodes is disclosed. Each compute node is connected to a same plurality of network compute nodes, such as compute-enabled network switches. Compute processes at the compute nodes generate local gradients or other vectors by, for instance, performing a forward pass on a neural network. Each vector comprises values for a same set of vector elements. Each network compute node is assigned to, based on the local vectors, reduce vector data for a different a subset of the vector elements. Each network compute node returns a result chunk for the elements it processed back to each of the compute nodes, whereby each compute node receives the full result vector. This configuration may, in some embodiments, reduce buffering, processing, and/or other resource requirements for the network compute node or network at large.

    ACTIVE CONTROL SYSTEM FOR DATA STREAM ALLOCATION
    7.
    发明公开
    ACTIVE CONTROL SYSTEM FOR DATA STREAM ALLOCATION 审中-公开

    公开(公告)号：US20230261966A1

    公开(公告)日：2023-08-17

    申请号：US17671075

    申请日：2022-02-14

    申请人： ADOBE INC.

    发明人： Georgios Theocharous ,  Kai Wang ,  Zhao Song ,  Sridhar Mahadevan

    IPC分类号： H04L45/00 ,  H04L41/147

    CPC分类号： H04L45/08 ,  H04L41/147

    摘要： A control system facilitates active management of a streaming data system. Given historical data traffic for each data stream processed by a streaming data system, the control system uses a machine learning model to predict future data traffic for each data stream. The control system selects a matching between data streams and servers for a future time that minimizes a cost comprising a switching cost and a server imbalance cost based on the predicted data traffic for the future time. In some configurations, the matching is selected using a planning window comprising a number of future time steps dynamically selected based on uncertainty associated with the predicted data traffic. Given the selected matching, the control system may manage the streaming data system by causing data streams to be moved between servers based on the matching.