公开(公告)号：US20230267096A1

公开(公告)日：2023-08-24

申请号：US18041168

申请日：2021-04-23

Applicant: QUALCOMM INCORPORATED

Inventor： Uttkarsh WARDHAN ,  Vishal GHORPADE ,  Sanku MUKHERJEE ,  Madan KRISHNAPPA ,  Sanath Sreekana BANGALORE ,  Pankhuri AGARWAL ,  Santanu PATTANAYAK

IPC: G06F15/78

CPC classification number: G06F15/781 ,  G06F15/7814

Abstract: The reliability of a data communication link may be analyzed and otherwise maintained by collecting a two-dimensional array representing a functional data eye, and using a convolutional neural network to determine a score of the functional data eye. The determined score may be compared with a threshold, and an action may be initiated based on the result of the comparison.

公开(公告)号：US20200293415A1

公开(公告)日：2020-09-17

申请号：US16354573

申请日：2019-03-15

Applicant: QUALCOMM Incorporated

Inventor： Sanku MUKHERJEE ,  Uttkarsh WARDHAN ,  Madan KRISHNAPPA

IPC: G06F11/22 ,  G06N20/00

Abstract: Certain aspects of the present disclosure generally relate to memory training. An example method generally includes assigning each of a plurality of data channels of a memory device to at least one processor, performing memory tests, in parallel, on the plurality of data channels by at least in part performing read and write operations on at least two or more of the plurality of data channels in parallel using the at least one processor, and determining a setting for one or more memory interface parameters associated with the memory device relative to a data eye for each of the plurality of data channels determined based on the memory tests.

公开(公告)号：US20220138613A1

公开(公告)日：2022-05-05

申请号：US17084508

申请日：2020-10-29

Applicant: QUALCOMM Incorporated

Inventor： Uttkarsh WARDHAN ,  Vishal GHORPADE ,  Sanku MUKHERJEE ,  Madan KRISHNAPPA ,  Pankhuri AGARWAL ,  Sanath Sreekanta BANGALORE ,  Santanu PATTANAYAK

IPC: G06N20/00

Abstract: A method performed by a machine learning system includes generating a set of reward values based on a set of parameter values selected by a machine learning system, each reward value of the set of reward values corresponding to a parameter value of the set of parameter values programmed at a device. The method also includes determining a reward function for maximizing a reward corresponding to a set of parameters of the device based on the set of reward values. The method further includes tuning a parameter of the set of parameters based on the reward function.