公开(公告)号：US20250071270A1

公开(公告)日：2025-02-27

申请号：US18791861

申请日：2024-08-01

Applicant: SigmaStar Technology Ltd.

Inventor： Shaobo ZHANG ,  Jianqiang DU ,  Chengwei ZHENG ,  Qun WANG ,  Zhenbao HUANG

IPC: H04N19/11 ,  H04N19/136 ,  H04N19/147 ,  H04N19/176 ,  H04N19/182 ,  H04N19/186 ,  H04N19/593

Abstract: A determination method for a chroma intra prediction mode includes: performing a simple RDO calculation on a luminance value of each pixel of an image block to obtain multiple luminance candidate modes; determining multiple chroma candidate modes according to one of the luminance candidate modes and a chroma simple RDO result calculated by performing a simple RDO calculation on a chroma value of each pixel of the image block; performing a full RDO calculation of the multiple luminance candidate modes on the luminance value of each pixel in the image block to select a luminance target mode; performing a full RDO calculation of the multiple chroma candidate modes on the chroma value of each pixel of the image block to a obtain chroma full RDO result; and determining a chroma target mode according to the luminance target mode and the chroma full RDO result.

公开(公告)号：US20220036162A1

公开(公告)日：2022-02-03

申请号：US17159217

申请日：2021-01-27

Applicant: Xiamen SigmaStar Technology Ltd.

Inventor： Tao XU ,  Chengwei ZHENG ,  Xiaofeng LI ,  Bo LIN

IPC: G06N3/04 ,  G06F17/18

Abstract: A network model quantization method includes: acquiring a target floating-point network model that is to be model quantized; determining an asymmetric quantization interval corresponding to an input value of the target floating-point network model; determining a symmetric quantization interval corresponding to a weight value of the target floating-point network model; and performing fixed-point quantization on the input value of the target floating-point network model according to the asymmetric quantization interval, and performing the fixed-point quantization on the weight value of the target floating-point network model according to the symmetric quantization interval to obtain a fixed-point network model corresponding to the target floating-point network model.

公开(公告)号：US20220092151A1

公开(公告)日：2022-03-24

申请号：US17328006

申请日：2021-05-24

Applicant: Xiamen SigmaStar Technology Ltd.

Inventor： Fabo BAO ,  Donghao LIU ,  Wei ZHU ,  Chengwei ZHENG

IPC: G06F17/15 ,  G06F9/54

Abstract: A convolution calculation apparatus applied for convolution calculation of a convolution layer includes a decompression circuit, a data combination circuit and a calculation circuit. The decompression circuit decompresses compressed weighting data of a convolution kernel of the convolution layer to generate decompressed weighting data. The data combination circuit combines the decompressed weighting data and non-compressed data of the convolution kernel to restore a data order of weighting data of the convolution kernel. The calculation circuit performs calculation according to the weighting data of the convolution kernel and input data of the convolution layer. Since the compressed weighting data of the convolution kernel is transmitted to the convolution calculation apparatus in advance, the compressed weighting data is first decompressed and then convolution calculation is performed accordingly, hence reducing the storage amount and transmission bandwidth used by the convolution kernel in an electronic apparatus.

公开(公告)号：US20210224033A1

公开(公告)日：2021-07-22

申请号：US17134660

申请日：2020-12-28

Applicant: Xiamen SigmaStar Technology Ltd.

Inventor： Xiaofeng LI ,  Chengwei ZHENG ,  Bo LIN

IPC: G06F7/483 ,  G06F9/30 ,  G06F17/15

Abstract: An operation device includes a quantizer circuit, a buffer circuit, a convolution core circuit and a multiply-add circuit. The quantizer circuit receives first feature data and performs asymmetric uniform quantization on the first feature data to obtain and store in the buffer circuit second feature data. The quantizer circuit further receives a first weighting coefficient and performs symmetric uniform quantization on the first weighting coefficient to obtain and store in the buffer circuit a second weight coefficient. The convolution core circuit performs a convolution operation on the initial operation result, an actual quantization scale factor and an actual bias value to obtain a final operation result.