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公开(公告)号：US11321901B2
公开(公告)日：2022-05-03
申请号：US16789870
申请日：2020-02-13
Applicant: MediaTek Inc.
Inventor： Chien-Chih Wang , Ying-Chieh Chen
Abstract: A graphics system includes an effect engine, which executes a predefined set of graphics operations having a higher computational complexity than pipeline operations. The graphics system further includes a graphics pipeline operative to perform the pipeline operations on graphical objects in a frame. The effect engine is operative to execute the predefined set of graphics operations on a subset of the graphical objects in the frame. One or more buffers are operative to receive pixels of the frame for display. The frame includes the graphical objects operated on by the graphics pipeline and the subset of the graphical objects operated on by the effect engine.
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Patent Agency Ranking
公开(公告)号：US11941741B2
公开(公告)日：2024-03-26
申请号：US17708965
申请日：2022-03-30
Applicant: MediaTek Inc.
Inventor： Chien-Chih Wang , Ying-Chieh Chen
CPC classification number: G06T15/005 , G06T1/20 , G06T15/06 , G06T1/60
Abstract: A graphics system includes an effect engine and a graphics pipeline. The graphics pipeline performs pipeline operations on graphical objects in a frame. The graphics pipeline includes at least a fragment shader stage. An application programming interface (API) provides an instruction that specifies a subset of the graphical objects in the frame for the effect engine to execute. When detecting the instruction, the graphics pipeline invokes the effect engine to perform a predefined set of graphics operations on the subset of the graphical objects in the frame. The predefined set of graphics operations has a higher computational complexity than the pipeline operations.
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公开(公告)号：US20210256753A1
公开(公告)日：2021-08-19
申请号：US16789870
申请日：2020-02-13
Applicant: MediaTek Inc.
Inventor： Chien-Chih Wang , Ying-Chieh Chen
Abstract: A graphics system includes an effect engine, which executes a predefined set of graphics operations having a higher computational complexity than pipeline operations. The graphics system further includes a graphics pipeline operative to perform the pipeline operations on graphical objects in a frame. The effect engine is operative to execute the predefined set of graphics operations on a subset of the graphical objects in the frame. One or more buffers are operative to receive pixels of the frame for display. The frame includes the graphical objects operated on by the graphics pipeline and the subset of the graphical objects operated on by the effect engine.
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公开(公告)号：US20220222885A1
公开(公告)日：2022-07-14
申请号：US17708965
申请日：2022-03-30
Applicant: MediaTek Inc.
Inventor： Chien-Chih Wang , Ying-Chieh Chen
Abstract: A graphics system includes an effect engine and a graphics pipeline. The graphics pipeline performs pipeline operations on graphical objects in a frame. The graphics pipeline includes at least a fragment shader stage. An application programming interface (API) provides an instruction that specifies a subset of the graphical objects in the frame for the effect engine to execute. When detecting the instruction, the graphics pipeline invokes the effect engine to perform a predefined set of graphics operations on the subset of the graphical objects in the frame. The predefined set of graphics operations has a higher computational complexity than the pipeline operations.
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公开(公告)号：US20240152194A1
公开(公告)日：2024-05-09
申请号：US18235351
申请日：2023-08-18
Applicant: MEDIATEK INC.
Inventor： Wen-Wen Hsieh , Ying-Yi Teng , Chien-Chih Wang
IPC: G06F1/3206
CPC classification number: G06F1/3206
Abstract: A power consumption reduction method can include defining y operation scenarios according to x types of extracted information, generating z power profiles each used for controlling power provided to a subset of a plurality of processors, assigning the z power profiles to the y operation scenarios in a machine learning model, collecting to-be-evaluated information by the plurality of processors, comparing the to-be-evaluated information with the x types of extracted information to find a most similar type of extracted information, using the machine learning model to select an optimal power profile from the z power profiles according to the most similar type of extracted information, and applying the optimal power profile to control the power provided to the subset of the plurality of processors. The subset of the plurality of processors are of the same type of processor. x, y and z can be an integer larger than zero.
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公开(公告)号：US20240119200A1
公开(公告)日：2024-04-11
申请号：US18375999
申请日：2023-10-03
Applicant: MEDIATEK INC.
Inventor： Yu-Jen Chen , Chien-Chih Wang , Wen-Wen Hsieh , Ying-Yi Teng
IPC: G06F30/27
CPC classification number: G06F30/27
Abstract: A method of building a characteristic model includes: acquiring raw electrical data from a measurement system outside one or more processing units; acquiring operational state-related data from an information collector inside the one or more processing units; performing a data annealing process on the raw electrical data and the operational state-related data to obtain and purified electrical data and purified operational state-related data; and performing a machine learning (ML)-based process to build the characteristic model based on the purified electrical data and the purified operational state-related data.
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