公开(公告)号：US20250156679A1

公开(公告)日：2025-05-15

申请号：US18945680

申请日：2024-11-13

Applicant: MEDIATEK INC.

Inventor： PING-YUAN TSENG ,  Jen-Chieh Tsai ,  Sheng-Je Hung ,  Chia-Wei Hsu ,  PO-YEN LIN ,  YEN-HAO CHEN

IPC: G06N3/042 ,  G06N3/0464

Abstract: The application discloses a compilation method, a data processing method and an apparatus thereof. Data representing a first graph characterizing the operations of a first neural network is obtained. The data representing the first graph is processed to transform the first graph into a second graph. A set of instructions for characterizing the second graph is generated. The set of instructions is provided to one or more hardware platforms.

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.