US 12,406,123 B2
System and method for ESL modeling of machine learning
Kai-Yuan Ting, Hsinchu (TW); Sandeep Kumar Goel, Hsinchu (TW); Tze-Chiang Huang, Hsichu (TW); and Yun-Han Lee, Hsinchu (TW)
Assigned to TAIWAN SEMICONDUCTOR MANUFACTURING COMPANY, LTD., Hsinchu (TW); and TSMC NANJING COMPANY, LIMITED, Nanjing (CN)
Filed by TAIWAN SEMICONDUCTOR MANUFACTURING COMPANY, LTD., Hsinchu (TW); and TSMC NANJING COMPANY, LIMITED, Nanjing (CN)
Filed on Jun. 17, 2024, as Appl. No. 18/745,089.
Application 18/745,089 is a division of application No. 17/115,407, filed on Dec. 8, 2020, granted, now 12,014,130.
Application 17/115,407 is a continuation of application No. 16/582,603, filed on Sep. 25, 2019, granted, now 10,867,098, issued on Dec. 15, 2020.
Claims priority of application No. 201910417773.2 (CN), filed on May 20, 2019.
Prior Publication US 2024/0338506 A1, Oct. 10, 2024
Int. Cl. G06F 30/39 (2020.01); G06N 20/00 (2019.01)
CPC G06F 30/39 (2020.01) [G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A non-transitory computer-readable storage medium encoded with a set of instructions for designing a semiconductor device using electronic system level (ESL) modeling for machine learning applications that, when executed by at least one processor, causes the at least one processor to:
retrieve a source code operable to execute a plurality of operations of a machine learning algorithm;
classify a first group of the plurality of operations as slow group operations and classify a second group of the plurality of operations as fast group operations, based on a time required to complete each operation;
define a neural network operable to execute the slow group operations;
define a trained neural network configuration including a plurality of interconnected neurons operable to execute the slow group operations; and
generate an ESL platform for evaluating a design of a semiconductor device based on the trained neural network configuration.