US 11,853,661 B2
Systems and methods for machine learning based fast static thermal solver
Norman Chang, Fremont, CA (US); Hsiming Pan, San Jose, CA (US); Jimin Wen, Pleasanton, CA (US); Deqi Zhu, San Jose, CA (US); Wenbo Xia, Milpitas, CA (US); Akhilesh Kumar, Milpitas, CA (US); Wen-Tze Chuang, Yilan County (TW); En-Cih Yang, New Taipei (TW); Karthik Srinivasan, Cupertino, CA (US); and Ying-Shiun Li, Pleasanton, CA (US)
Assigned to ANSYS, INC., Canonsburg, PA (US)
Filed by ANSYS, INC., Canonsburg, PA (US)
Filed on May 20, 2022, as Appl. No. 17/664,241.
Application 17/664,241 is a division of application No. 16/709,746, filed on Dec. 10, 2019, granted, now 11,366,947.
Prior Publication US 2022/0277120 A1, Sep. 1, 2022
Int. Cl. G06F 30/27 (2020.01); G06F 119/08 (2020.01); G06F 113/18 (2020.01)
CPC G06F 30/27 (2020.01) [G06F 2113/18 (2020.01); G06F 2119/08 (2020.01)] 14 Claims
OG exemplary drawing
 
1. A non-transitory machine readable medium storing executable program instructions which when executed by a data processing system cause the data processing system to perform a method, the method comprising:
retrieving from memory, a trained neural network model, the neural network model having been trained with a plurality of inputs and an output derived from thermal simulations, the plurality of inputs comprising a relationship between a change in temperature relative to power, a predetermined template location, and a pattern of a plurality of predefined power levels in tiles associated with the template; and
determining, using the retrieved trained neural network model, a change in a temperature of a given tile on an integrated circuit (IC) having a location relative to the predetermined template location, a plurality of inputs to the neural network model including: (1) a selected relationship between a change in temperature relative to a power applied to the IC in the thermal simulations, (2) a selected predetermined location of the template, and (3) a selected pattern of a predefined power level for the template.