US 11,748,536 B2
Automated microprocessor design
Yunsup Lee, Redwood City, CA (US); and Michael Cave, San Mateo, CA (US)
Assigned to SiFive, Inc., San Mateo, CA (US)
Appl. No. 17/297,745
Filed by SiFive, Inc., San Mateo, CA (US)
PCT Filed Nov. 27, 2019, PCT No. PCT/US2019/063603
§ 371(c)(1), (2) Date May 27, 2021,
PCT Pub. No. WO2020/112999, PCT Pub. Date Jun. 4, 2020.
Claims priority of provisional application 62/772,626, filed on Nov. 28, 2018.
Prior Publication US 2022/0050946 A1, Feb. 17, 2022
Int. Cl. G06F 30/327 (2020.01); G06F 30/33 (2020.01); G06F 115/02 (2020.01); G06F 115/12 (2020.01)
CPC G06F 30/327 (2020.01) [G06F 30/33 (2020.01); G06F 2115/02 (2020.01); G06F 2115/12 (2020.01)] 7 Claims
OG exemplary drawing
 
1. A system comprising:
a web application server configured to generate a design parameters data structure based on input received, wherein the design parameters data structure includes values of design parameters of an integrated circuit design, configured to display an auto-updating block diagram of a template design reflecting changes to values of the design parameters of the integrated circuit design, and configured to issue a command to build the integrated circuit design; and
a controller configured to, responsive to the command to build the integrated circuit design, access the design parameters data structure, invoke a register-transfer level service module with the design parameters data structure to obtain a register-transfer level data structure, invoke a software development kit service module with the register-transfer level data structure to obtain a software development kit, invoke a physical design service module with the register-transfer level data structure to obtain a physical design data structure, invoke a verification service module to obtain a test plan, and invoke tests for the integrated circuit design based on the test plan, the register-transfer level data structure, the software development kit, and the physical design data structure to obtain a set of test results; and
a machine learning based design iterator configured to take as input both, values of design parameters of the design parameters data structure, and a feedback signal based on a design criterion of the design parameters data structure and the set of test results, to obtain a modified design parameters data structure, and configured to issue a command to the controller to cause the controller to build a second integrated circuit design based on the modified design parameters data structure.