IP Library Granted Patent US 8,631,362
Granted Patent B1
US 8,631,362 · App. 13/776,598 · Granted Jan 14, 2014

Circuit instance variation probability system and method

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Quick Facts
Patent No.
US 8,631,362
App. No.
13/776,598
Granted
Jan 14, 2014
Kind
B1
Abstract

A system and process for utilizing probability distribution information about process parameters to quantify the probability of manufacturing process variation for variants of circuit designs in order to more efficiently analyze and simulate the designs.

Claims (32)

1. A computer based method for quantifying the probability of a circuit design variant comprising:

receiving a circuit netlist related to the circuit design variant;

identifying a process parameter vector from said circuit netlist, comprising a set of manufacturing process parameters, wherein each process parameter has an associated process parameter distribution;

determining by the computer a process probability distribution function based upon the process parameter distribution;

determining a circuit design variant probability for the circuit design variant based on the process probability distribution function;

storing said circuit design variant probability information.

2. The computer based method of claim 1 , wherein said step of determining a process probability distribution function uses a process Monte Carlo.

3. The computer based method of claim 1 , wherein said step determining the circuit design variant probability is one of a relative probability and an absolute probability.

4. The computer based method of claim 3 , wherein the likelihood of each process probability distribution function occurring is determined using said the associated process parameter distributions.

5. The computer based method of claim 4 , wherein said process parameter vector includes one or more process parameters from said circuit netlist.

6. The computer based method of claim 4 , wherein said step of generating a circuit design variant probability comprises:

determining a value for a selected process parameter vector representing a distance of said selected process parameter vector from a central value of said process probability distribution function.

7. The computer based method of claim 1 , wherein said step determining the circuit design variant probability is one of a relative probability and an absolute probability.

8. The computer based method of claim 1 , wherein the likelihood of each process probability distribution function occurring is determined using said the associated process parameter distributions.

9. The computer based method of claim 1 , wherein said process parameter vector includes one or more process parameters from said circuit netlist.

10. The computer based method of claim 1 , wherein said step of generating a circuit design variant probability comprises:

determining a value for a selected process parameter vector representing a distance of said selected process parameter vector from a central value of said process probability distribution function.

11. The computer based method of claim 10 , wherein said distance is determined using Euclidean distance.

12. The computer based method of claim 10 , wherein said central value is the mean of said process probability distribution function.

13. A non-transitory computer readable medium comprising instructions which when executed by a processor perform the steps of:

receiving a circuit netlist related to a circuit design variant;

identifying a process parameter vector from said circuit netlist, comprising a set of manufacturing process parameters, wherein each process parameter has an associated process parameter distribution;

determining a process probability distribution function based upon the process parameter distribution;

determining a circuit design variant probability for the circuit design variant based on the process probability distribution function;

storing said circuit design variant probability information.

14. The non-transitory computer readable medium of claim 13 , wherein said step of determining a process probability distribution function uses a process Monte Carlo.

15. The non-transitory computer readable medium of claim 13 , wherein said step determining the circuit design variant probability is one of a relative probability and an absolute probability.

16. The non-transitory computer readable medium of claim 13 , wherein the likelihood of each process probability distribution function occurring is determined using said the associated process parameter distributions.

17. The non-transitory computer readable medium of claim 13 , wherein said process parameter vector includes one or more process parameters from said circuit netlist.

18. The non-transitory computer readable medium of claim 13 , wherein said step of generating a circuit design variant probability comprises:

determining a value for a selected process parameter vector representing a distance of said selected process parameter vector from a central value of said process probability distribution function.

19. The non-transitory computer readable medium of claim 13 , wherein said step determining the circuit design variant probability is one of a relative probability and an absolute probability.

Assignments (3)
MERGER AND CHANGE OF NAME Recorded Jun 24, 2021
From: MENTOR GRAPHICS CORPORATION; SIEMENS INDUSTRY SOFTWARE INC.
To: SIEMENS INDUSTRY SOFTWARE INC.
Reel/Frame 056675/0285 →
NUNC PRO TUNC ASSIGNMENT Recorded Aug 31, 2015
From: BERKELEY DESIGN AUTOMATION, INC.
To: MENTOR GRAPHICS CORPORATION
Reel/Frame 036456/0918 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 1, 2013
From: MEHROTRA, AMIT; SOMANI, ABHISHEK; JOHNSON, KURT; ESTRADA, PAUL
To: BERKELEY DESIGN AUTOMATION, INC.
Reel/Frame 029909/0712 →