公开(公告)号：US20230177349A1

公开(公告)日：2023-06-08

申请号：US17920839

申请日：2021-05-29

申请人： Intel Corporation

发明人： Ravikumar Balakrishnan ,  Nageen Himayat ,  Mustafa Riza Akdeniz ,  Sagar Dhakal ,  Arjun Anand ,  Hesham Mostafa

IPC分类号： G06N3/098 ,  H04L67/10

CPC分类号： G06N3/098 ,  H04L67/10

摘要： The apparatus of an edge computing node, a system, a method and a machine-readable medium. The apparatus includes a processor to cause an initial set of weights for a global machine learning (ML) model to be transmitted a set of client compute nodes of the edge computing network; process Hessians computed by each of the client compute nodes based on a dataset stored on the client compute node; evaluate a gradient expression for the ML model based on a second dataset and an updated set of weights received from the client compute nodes; and generate a meta-updated set of weights for the global model based on the initial set of weights, the Hessians received, and the evaluated gradient expression.

公开(公告)号：US12021720B2

公开(公告)日：2024-06-25

申请号：US16937267

申请日：2020-07-23

申请人： Intel Corporation

发明人： Ajay Gupta ,  Ravikumar Balakrishnan ,  Shahrnaz Azizi ,  Maruti Gupta Hyde ,  Ariela Zeira ,  Arjun Anand ,  Jacob Winick

IPC分类号： H04L43/0852 ,  G06F1/3203 ,  H04L47/10 ,  H04L47/50

CPC分类号： H04L43/0852 ,  G06F1/3203 ,  H04L47/10 ,  H04L47/50

摘要： Methods, apparatus, systems, and articles of manufacture are disclosed that generate dynamic latency values. An example apparatus includes an active status controller to determine that a modem is active based on a number of packets obtained from a network, a prediction controller to predict that the number of packets are indicative of a workload type based on a trained model, and a latency value generator to generate a latency value based on the workload type of the number of packets, the latency value to cause a processor processing the number of packets to enter a power saving state or a power executing state.

公开(公告)号：US20230068386A1

公开(公告)日：2023-03-02

申请号：US17790950

申请日：2020-12-26

申请人： Intel Corporation

发明人： Mustafa Riza Akdeniz ,  Arjun Anand ,  Nageen Himayat ,  Amir S. Avestimehr ,  Ravikumar Balakrishnan ,  Prashant Bhardwaj ,  Jeongsik Choi ,  Yang-Seok Choi ,  Sagar Dhakal ,  Brandon Gary Edwards ,  Saurav Prakash ,  Amit Solomon ,  Shilpa Talwar ,  Yair Eliyahu Yona

IPC分类号： G06N20/00

摘要： The apparatus of an edge computing node, a system, a method and a machine-readable medium. The apparatus includes a processor to perform rounds of federated machine learning training including: processing client reports from a plurality of clients of the edge computing network; selecting a candidate set of clients from the plurality of clients for an epoch of the federated machine learning training; causing a global model to be sent to the candidate set of clients; and performing the federated machine learning training on the candidate set of clients. The processor may perform rounds of federated machine learning training including: obtaining coded training data from each of the selected clients; and performing machine learning training on the coded training data.

公开(公告)号：US20240155025A1

公开(公告)日：2024-05-09

申请号：US18550856

申请日：2022-06-09

申请人： Intel Corporation

发明人： Mustafa Riza Akdeniz ,  Arjun Anand ,  Ravikumar Balakrishnan ,  Sagar Dhakal ,  Nageen Himayat

IPC分类号： H04L67/10 ,  G06F17/18 ,  H04L67/289

CPC分类号： H04L67/10 ,  G06F17/18 ,  H04L67/289

摘要： An apparatus of an edge computing node, a method, and a machine-readable storage medium. The apparatus is to decode messages from a plurality of clients within the edge computing network, the messages including respective coded data for respective ones of the plurality of clients; computing estimates of metrics related to a global model for federated learning using the coded data, the metrics including a gradient on the coded data; use the metrics to update the global model to generate an updated global model, wherein the edge computing node is to update the global model by calculating the gradient on the coded data based on a linear fit of the global model to estimated labels from the federated learning; and send a message including the updated global model for transmission to at least some of the clients.

公开(公告)号：US11917655B2

公开(公告)日：2024-02-27

申请号：US16727271

申请日：2019-12-26

申请人： INTEL CORPORATION

发明人： Arjun Anand ,  Vinod Kristem ,  Rath Vannithamby

IPC分类号： H04W4/00 ,  H04W72/52 ,  H04L5/00

CPC分类号： H04W72/52 ,  H04L5/0007

摘要： For example, a wireless communication device may be configured to determine a Resource Unit (RU) allocation of a plurality of RUs to a plurality of wireless communication stations (STAs), respectively, the RU allocation to allocate to a STA of the plurality of STAs an RU of the plurality of RUs, wherein an RU size of the RU allocated to the STA is based at least on a traffic rate parameter, which is dependent on a traffic rate of Downlink (DL) traffic for the STA; and to transmit a Multi-User (MU) DL Orthogonal-Frequency-Division-Multiple-Access (OFDMA) Physical-layer Protocol Data Unit (PPDU) to the plurality of STAs according to the RU allocation.

公开(公告)号：US20220377614A1

公开(公告)日：2022-11-24

申请号：US17712050

申请日：2022-04-01

申请人： Intel Corporation

发明人： Ravikumar Balakrishnan ,  Nageen Himayat ,  Arjun Anand ,  Mustafa Riza Akdeniz ,  Sagar Dhakal ,  Mark R. Eisen ,  Navid Naderializadeh

IPC分类号： H04W28/08 ,  H04W28/02

摘要： An apparatus of a transmitter computing node n (TX node n) of a wireless network, one or more computer readable media, a system, and a method. The apparatus includes one or more processors to: implement machine learning (ML) based training rounds, each training round including: determining a local action value function Qn(hn, an; θn) corresponding to a value of performing a radio resource management (RRM) action an at a receiving computing node n (RX node n) associated with TX node n using policy parameter θn and based on hn, hn including channel state information at RX node n; and determining, based on an overall action value function Qtot at time t, an estimated gradient of an overall loss at time t for overall policy parameter θt(∇Lt(θt)), wherein Qtot corresponds to a mixing of local action value functions Qi(hi, ai; θi) for all TX nodes i in the network at time t including TX node n; and determine, in response to a determination that ∇Lt(θt) is close to zero for various values of t during training, a trained local action value function Qn,trained to generate a trained action value relating to data communication between TX node n and RX node n.

公开(公告)号：US20220007382A1

公开(公告)日：2022-01-06

申请号：US17479991

申请日：2021-09-20

申请人： Intel Corporation

发明人： Arjun Anand ,  Ravikumar Balakrishnan ,  Vallabhajosyula S. Somayazulu ,  Rath Vannithamby

IPC分类号： H04W72/12 ,  G06N3/08 ,  G06N3/04

摘要： In one embodiment, an apparatus of an access point (AP) node of a network includes an interconnect interface to connect the apparatus to one or more components of the AP node and a processor to: access scheduling requests from a plurality of devices, select a subset of the devices for scheduling of resource blocks in a time slot, and schedule wireless resource blocks in the time slot for the subset of devices using a neural network (NN) trained via deep reinforcement learning (DRL).

公开(公告)号：US20210204291A1

公开(公告)日：2021-07-01

申请号：US16727271

申请日：2019-12-26

申请人： INTEL CORPORATION

发明人： Arjun Anand ,  Vinod Kristem ,  Rath Vannithamby

IPC分类号： H04W72/04 ,  H04L5/00

摘要： For example, a wireless communication device may be configured to determine a Resource Unit (RU) allocation of a plurality of RUs to a plurality of wireless communication stations (STAs), respectively, the RU allocation to allocate to a STA of the plurality of STAs an RU of the plurality of RUs, wherein an RU size of the RU allocated to the STA is based at least on a traffic rate parameter, which is dependent on a traffic rate of Downlink (DL) traffic for the STA; and to transmit a Multi-User (MU) DL Orthogonal-Frequency-Division-Multiple-Access (OFDMA) Physical-layer Protocol Data Unit (PPDU) to the plurality of STAs according to the RU allocation.