Method and apparatus for designing electronic circuits using optimization

• US 7,516,423 B2
• Filed: 07/13/2004
• Issued: 04/07/2009
• Est. Priority Date: 07/13/2004
• Status: Expired due to Fees

• Current Assignee: Kimotion Technologies, Inc.
• Original Assignee: Kimotion Technologies, Inc.
• Inventors: Sorensen, Bendt, Lauwers, Erik, Verhaegen, Wim, Daems, Walter, De Smedt, Bart
• Primary Examiner(s): Dinh; Paul
• Application Number:
  US10/890,349
• Publication Number:
  US 20060015829A1
• Time in Patent Office: 1,729 Days
• Field of Search: 716 1- 5, 716/7, 703 2- 3, 703/28, 700/28
• US Class Current: 716/132
• CPC Class Codes: G06F 2111/06 Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]
• CPC Class Codes: G06F 30/327 Logic synthesis; Behaviour synthesis, e.g. mapping logic, HDL to netlist, high-level language to RTL or netlist

Abstract

Methods and apparatus for designing electronic circuits, including analog and mixed signal (AMS) circuits, based on an evolutionary optimization approach. In one exemplary embodiment, the optimization approach is implemented using a computer program running on one or more computers. The optimization program receives inputs from the designer regarding (i) optimization objectives for the design process, and (ii) the constraint mechanisms to be applied. Both constrained and unconstrained optimization formulations can be addressed by the program. Various objective function evaluation mechanisms are implemented. The program also advantageously allows for continuously encoded variables, which are particularly useful for solving AMS design problems.

Claims

1. A method of designing an electronic circuit using a design process comprising:

formulating an optimization problem, said optimization problem comprising a plurality of design variables relating to said electronic circuit and defining at least one design objective;

identifying one or more decorrelations between two or more of said design variables, said identifying one or more decorrelations comprising at least dividing a search space associated with said optimization problem into a plurality of partitions and evaluating said partitions;

generating, using a computerized system, an optimized solution to said problem using an evolutionary process, said act of generating based at least in part on said act of identifying; and

using said solution to implement at least a portion of hardware or logic associated with said circuit.

2. The method of claim 1, wherein said act of formulating further comprises:

defining at least one constraint; and

defining at least one constraint handling mechanism.

3. The method of claim 1, wherein said act of generating comprises:

providing at least one set of candidate solutions;

evaluating said at least one objective for said at least one set; and

selecting at least one subset from said at least one set based at least in part on said act of evaluating.

4. The method of claim 3, wherein said act of generating further comprises constructing at least one model based at least in part on said at least one selected subset.

5. The method of claim 4, wherein said act of generating further comprises constructing at least one new set of candidate solutions based at least in part on said at least one model.

6. The method of claim 5, wherein said act of constructing at least one model comprises constructing said model in an incremental fashion during the design process.

7. The method of claim 4, wherein said act of constructing at least one model comprises constructing at least one stochastic model.

8. The method of claim 4, wherein said act of constructing is at least partly performed over a computer network having a plurality of computers in data communication therewith.

9. The method of claim 3, wherein said act of evaluating is at least partly performed over a computer network having a plurality of computers in data communication therewith.

10. The method of claim 1, wherein said electronic circuit comprises an AMS circuit.

11. The method of claim 10, wherein said act of generating is at least partly performed over a computer network having a plurality of computers in data communication therewith.

12. The method of claim 1, wherein said act of generating comprises encoding continuous optimization variables.

13. The method of claim 12, wherein said act of generating further comprises encoding discrete optimization variables along with said continuous variables.

14. The method of claim 1, further comprising applying at least one mutation operator during at least a portion of said act of generating.

15. The method of claim 1, wherein said act of generating further comprises selectively favoring more distributed sets of candidate solutions, either as an intermediate or as a final step to accomplish proper convergence.

16. A computer readable medium adapted to store a plurality of data thereon, said plurality of data comprising at least one computer program, said at least one program being adapted to generating a design of an electronic circuit by at least:

formulating an optimization problem, said act of formulating comprising defining at least one design objective; and

optimizing said optimization problem based at least in part on an evolutionary optimization methodology, said methodology comprising;

providing a set of candidate solutions;

evaluating at least a portion of said solutions based at least in part on said at least one objective;

selecting at least one subset of candidate solutions from said set, said act of selecting comprising identifying one or more decorrelations between two or more design variables associated with said optimization problem by dividing a search space associated with said optimization problem into a plurality of partitions, and continuing said dividing until a model limitation is reached; and

utilizing at least a portion of said at least one subset of candidate solutions to generate said design of said circuit.

17. The computer readable medium of claim 16, wherein said medium comprises a hard disk drive (HDD) of a computer system.

18. The computer readable medium of claim 16, wherein said at least one program is adapted to communicate with other programs distributed across multiple processing entities of a computer network.

19. The computer readable medium of claim 18, wherein said at least one program comprises a server portion of a distributed application having at least one client portion.

20. The computer readable medium of claim 18, wherein said network comprises a peer-to-peer network.