公开(公告)号：US11907328B2

公开(公告)日：2024-02-20

申请号：US17192469

申请日：2021-03-04

Applicant: Samsung Electronics Co., Ltd.

Inventor： Weiran Deng ,  Zhengping Ji

IPC: G06F17/15 ,  G06F7/556 ,  G06F7/544 ,  G06N3/063 ,  G06F30/398 ,  G06N3/045

CPC classification number: G06F17/15 ,  G06F7/5443 ,  G06F7/556 ,  G06F30/398 ,  G06N3/045 ,  G06N3/063

Abstract: A method of manufacturing an apparatus is provided. The apparatus is formed on a wafer or a package. The apparatus includes a polynomial generator, a plurality of matrix generators connected to an output of the polynomial generator, and a convolution generator connected to an output of the plurality of matrix generators. The apparatus is tested using one or more electrical to optical converters, one or more optical splitters, and one or more optical to electrical converters.

公开(公告)号：US20230153580A1

公开(公告)日：2023-05-18

申请号：US17900522

申请日：2022-08-31

Applicant: Samsung Electronics Co., Ltd.

Inventor： Weiran Deng

IPC: G06N3/047

CPC classification number: G06N3/047

Abstract: A method includes: providing a deep neural networks (DNN) model comprising a plurality of layers, each layer of the plurality of layers includes a plurality of nodes; sampling a change of a weight for each of a plurality of weights based on a distribution function, each weight of the plurality of weights corresponds to each node of the plurality of nodes; updating the weight with the change of the weight multiplied by a sign of the weight; and training the DNN model by iterating the steps of sampling the change and updating the weight. The plurality of weights has a high rate of sparsity after the training.

公开(公告)号：US11151428B2

公开(公告)日：2021-10-19

申请号：US16844572

申请日：2020-04-09

Applicant: Samsung Electronics Co., Ltd.

Inventor： Georgios Georgiadis ,  Weiran Deng

IPC: G06K9/66 ,  G06K9/62 ,  G06N3/08

Abstract: A system and method for pruning. A neural network includes a plurality of long short-term memory cells, each of which includes an input having a weight matrix Wc, an input gate having a weight matrix Wi, a forget gate having a weight matrix Wf, and an output gate having a weight matrix Wo. In some embodiments, after initial training, one or more of the weight matrices Wi, Wf, and Wo are pruned, and the weight matrix Wc is left unchanged. The neural network is then retrained, the pruned weights being constrained to remain zero during retraining.

公开(公告)号：US20210192009A1

公开(公告)日：2021-06-24

申请号：US17192469

申请日：2021-03-04

Applicant: Samsung Electronics Co., Ltd.

Inventor： Weiran Deng ,  Zhengping Ji

IPC: G06F17/15 ,  G06F7/556 ,  G06F7/544 ,  G06N3/04 ,  G06N3/063 ,  G06F30/398

Abstract: A method of manufacturing an apparatus is provided. The apparatus is formed on a wafer or a package, The apparatus includes a polynomial generator, a plurality of matrix generators connected to an output of the polynomial generator, and a convolution generator connected to an output of the plurality of matrix generators. The apparatus is tested using one or more electrical to optical converters, one or more optical splitters, and one or more optical to electrical converters.

公开(公告)号：US10387533B2

公开(公告)日：2019-08-20

申请号：US15611342

申请日：2017-06-01

Applicant: Samsung Electronics Co., Ltd.

Inventor： Weiran Deng ,  Zhengping Ji

IPC: G06F17/50 ,  G06F17/15 ,  G06F7/556 ,  G06F7/544

Abstract: An apparatus and a method is provided. The apparatus includes a polynomial generator, including an input and an output; a first matrix generator, including an input connected to the output of the polynomial generator, and an output; a second matrix generator, including an input connected to the output of the first matrix generator, and an output; a third matrix generator, including a first input connected to the output of the first matrix generator, a second input connected to the output of the second matrix generator, and an output; and a convolution generator, including an input connected to the output of the third matrix generator, and an output.