公开(公告)号：US20250068938A1

公开(公告)日：2025-02-27

申请号：US18426830

申请日：2024-01-30

Applicant: Samsung Electronics Co., Ltd. ,  Seoul National University R&DB Foundation

Inventor： Minje KIM ,  Jaejin LEE ,  Dohun KIM ,  Jinpyo KIM ,  Soon-Wan KWON ,  Heehoon KIM ,  Daeyoung PARK

IPC: G06N5/022 ,  G06F1/3203 ,  G06N3/04

Abstract: A processor-implemented method includes obtaining a benchmark execution result, receiving input data comprising a neural network model subject to prediction and analysis requirement information, receiving information on hardware of a device in which the neural network model is run, building a prediction model based on the benchmark execution result and the hardware information, extracting layer information respectively corresponding to a plurality of layers configuring the neural network model, and predicting either one or both of operation performance information and energy efficiency information respectively corresponding to the plurality of layers by inputting the analysis requirement information and the layer information to the prediction model.

公开(公告)号：US20220207431A1

公开(公告)日：2022-06-30

申请号：US17460698

申请日：2021-08-30

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Daeyoung PARK ,  Changwook JEONG ,  Moonhyun CHA

IPC: G06N20/20 ,  G06K9/62

Abstract: A computer-implemented method of training a teacher model and a student model includes dividing the teacher model into a series of teacher blocks each comprising at least one layer; generating a first student branch receiving a first feature output from a first teacher block among the series of teacher blocks; training the teacher model based on outputs of the teacher model and the first student branch; and training the student model comprising a series of student blocks based on the trained teacher model, wherein the first student branch includes at least one student block.