公开(公告)号：US20240119283A1

公开(公告)日：2024-04-11

申请号：US18377315

申请日：2023-10-06

Applicant: MEDIATEK INC.

Inventor： Jui-Yang Hsu ,  Cheng-Sheng Chan ,  Jen-Chieh Tsai ,  Huai-Ting Li ,  Bo-Yu Kuo ,  Yen-Hao Chen ,  Kai-Ling Huang ,  Ping-Yuan Tseng ,  Tao Tu ,  Sheng-Je Hung

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: A method of performing automatic tuning on a deep learning model includes: utilizing an instruction-based learned cost model to estimate a first type of operational performance metrics based on a tuned configuration of layer fusion and tensor tiling; utilizing statistical data gathered during a compilation process of the deep learning model to determine a second type of operational performance metrics based on the tuned configuration of layer fusion and tensor tiling; performing an auto-tuning process to obtain a plurality of optimal configurations based on the first type of operational performance metrics and the second type of operational performance metrics; and configure the deep learning model according to one of the plurality of optimal configurations.

公开(公告)号：US20250156721A1

公开(公告)日：2025-05-15

申请号：US18940856

申请日：2024-11-08

Applicant: MEDIATEK INC.

Inventor： Chun-Wei Yang ,  Bo-Yu Kuo ,  Cheng-Sheng Chan ,  Sheng-Je Hung

IPC: G06N3/092

Abstract: A neural network optimization method includes: executing a population-based algorithm to tune and evaluate a policy group, in order to generate one or more evaluation results, wherein the policy group comprises one or more policies, and each of the one or more policies is related to a neural network; executing a learning-based algorithm to tune the one or more policies according to the one or more evaluation results, to generate one or more tuned policies; performing an inference operation according to a target neural network and the one or more tuned policies, to generate multiple configuration candidates; and performing a selection operation upon the multiple configuration candidates to generate an optimal configuration, for outputting to a compiler and generating an optimized neural network, wherein the optimized neural network is an optimized version of the target neural network.

公开(公告)号：US20250156708A1

公开(公告)日：2025-05-15

申请号：US18939492

申请日：2024-11-06

Applicant: MEDIATEK INC.

Inventor： Tzu-Yun Chien ,  Bo-Yu Kuo ,  Jui-Yang Hsu ,  Kai-Ling Huang ,  Sheng-Je Hung

IPC: G06N3/08

Abstract: A method for optimizing deep learning models includes: initializing a plurality of pools, each including a plurality of candidate solutions; concurrently performing a plurality of tuning algorithms respectively within the plurality of pools during a single tuning run, thereby obtaining a plurality of selected candidate solutions; and generating an optimized model configuration based on the plurality of selected candidate solutions.