发明申请
WO2022232679A1 MULTI-ALGORITHMIC APPROACH TO REPRESENT HIGHLY NON-LINEAR HIGH DIMENSIONAL SPACE
审中-公开
基本信息:
- 专利标题: MULTI-ALGORITHMIC APPROACH TO REPRESENT HIGHLY NON-LINEAR HIGH DIMENSIONAL SPACE
- 申请号:PCT/US2022/027209 申请日:2022-05-02
- 公开(公告)号:WO2022232679A1 公开(公告)日:2022-11-03
- 发明人: GUPTA, Nikhil , FISCHER, Timothy, W. , KHANDELWAL, Ashish , KODURI, Sreenivasan, K.
- 申请人: TEXAS INSTRUMENTS INCORPORATED
- 申请人地址: P.O. Box 655474, Mail Station 3999
- 专利权人: TEXAS INSTRUMENTS INCORPORATED
- 当前专利权人: TEXAS INSTRUMENTS INCORPORATED
- 当前专利权人地址: P.O. Box 655474, Mail Station 3999
- 代理机构: ABRAHAM, Ebby
- 优先权: US17/245,306 2021-04-30
- 主分类号: G06F30/27
- IPC分类号: G06F30/27 ; G06F30/38
摘要:
A technique for designing circuits including receiving a data object (514) representing a circuit for a first process technology, the circuit including a first sub-circuit, the first sub-circuit including a first electrical component and a second electrical component arranged in a first topology; identifying the first sub-circuit in the data object (518) by comparing the first topology to a stored topology, the stored topology associated with the first process technology; identifying a first set of physical parameter values associated with first electrical component and the second electrical component of the first sub-circuit; determining a set of performance parameter values (520) for the first sub-circuit based on a first machine learning model of the first sub-circuit and the identified set of physical parameters; converting the identified first sub-circuit to a second sub-circuit (522) for the second process technology based on the determined set of performance parameter values; and outputting the second sub-circuit (526).
IPC结构图谱:
G06F30/27 | 使用机器学习,例如人工智能,神经网络,支持向量机 |