公开(公告)号：US20210119882A1

公开(公告)日：2021-04-22

申请号：US17133513

申请日：2020-12-23

Applicant: Intel Corporation

Inventor： Oner Orhan ,  Shilpa Talwar ,  Marcel Nassar ,  Hosein Nikopour ,  Meryem Simsek ,  Oguz Elibol

IPC: H04L12/24 ,  H04L5/00 ,  G06N20/00

Abstract: Methods, apparatus, systems and articles of manufacture to determine topologies for networks are disclosed. An example a non-transitory computer readable medium comprises instructions that, when executed, cause a machine to at least: determine link capacities for a plurality of links between nodes of a network, determine a maximum number of children of the peer linked nodes, determine a maximum number of parents of the peer linked nodes, and utilize reinforcement learning to determine a subset of the plurality of links to be activated in the network based on the link capacities, the maximum number of children, and the maximum number of parents.

公开(公告)号：US11216719B2

公开(公告)日：2022-01-04

申请号：US16009456

申请日：2018-06-15

Applicant: INTEL CORPORATION

Inventor： Somdeb Majumdar ,  Ron Banner ,  Marcel Nassar ,  Lior Storfer ,  Adnan Agbaria ,  Evren Tumer ,  Tristan Webb ,  Xin Wang

IPC: G06N3/04 ,  G06N3/08 ,  G06N3/063

Abstract: Logic may quantize a primary neural network. Logic may generate, by a secondary neural network logic circuitry for a primary neural network logic circuitry, quantization parameters. The primary neural network logic circuitry may comprise a primary neural network with multiple layers trainable with an objective function. Each of the multiple layers of the primary neural network may comprise multiple tensors. The secondary neural network logic circuitry may comprise one or more secondary neural networks trainable with the objective function to output the quantization parameters to the tensors.