Layman Description: Computers have been assisting humans in design of artifacts for several years now, such as design of aircraft or design of Integrated Circuits. We demonstrate one such tool that can assist engineers to build standard cells on-the-fly customized to criteria specified by them. We use genetic algorithms to guide the computer. This starts with an engineer providing the desired output signals. The computer program then randomly generates say 10,000 possible design configurations. Good designs are then Selected from this population of designs (priority given to designs that bettter meet the engineers' output requirement). Hybrid designs are developed using genetic operators. Heres where it gets interesting. Unlike most traditional computer programs, the genetic algorithm create a hybrid design by a "Crossover" of two good "Parent" designs (creating, hopefully, a better design) or random "Mutations" of good designs. These genetic operators are used on the initial population of 10,000 designs to create a second population of another (say) 10,000 designs. What happens when you do this 1000s of times? Do you arrive at the "perfect" (optimized) design? Thats what this work is about. ACKNOWLEDGEMENT This work at the AI CENTER & DEPT. OF COMPUTER SCIENCE & UNI OF GEORGIA in 2001 demonstrated designs an Inverter Standard Cell on-the-fly. It was sponsored by a YAMACRAW grant from the STATE OF GEORGIA, UNITED STATES. TECHNICAL DESCRIPTION The problem of designing the transistor-level layout of cells in a standard cell library is a multi-objective design optimization problem. Contemporary methods are optimization or compaction engines that rely on a schematic representation supplied by a design engineer. We have demonstrated the possibility of applying a modified genetic algorithm (GADO) to design a cell given only a behavioral description. A working inverter is designed as a proof of concept along with other inverters with arbitrary label placements. This is an example of design without human intervention, i.e. a computer design as opposed to a computer-aided design.

1. An Evolutionary approach to Standard Cell Design: a proof of concept Anil Bahuman Artificial Intelligence Center University of Georgia July 2001

5. Research Goal Truth Table Layout with “minimum” area “ Schematic and layout are designed in parallel” Explore possibility of automating the design of simple logic standard cells by exploring design spaces not considered by human designers 1 0 1 0 0 1 Out In

7. Design Example

8. A Transistor in MAGIC

9. Error tiles indicating DRC Errors

10. An Inverter in MAGIC Lambda, cell limits, labels, template, inputs, output, gate, terminals, wires, poly, contacts, 3I - 1O

11. SPICE simulation of the Inverter

12. Research Goal

13. Research Goal – Inverter Truth Table Layout with “minimum” area “ Schematic and layout are designed in parallel” 1 0 1 0 0 1 Out In

15. Architecture

16. architecture MAGIC SPICE Modified GADO (DRC ERRORS , AREA) (CORRECTNESS) DESIGN ENGINE EVALUATOR DESIGN RULE CHECKER CIRCUIT SIMULATOR Fitness module (CIRCUIT FILE)

19. 11 Building Blocks

20. Encoding an Object A B 14 0 Cell limits Y 15 0 Cell limits X 5 0 Cell limits Stretch Factor 2 0 0-3 Orientation 11 11 1-15 Object Type B A VALUE PARAMETER

21. An Individual Y X Stretch Factor Orientation Object Type

22. Connections b/w Transistors terminal

25. Sample Cell Corresponding Graph

26. Results

27. Success 1

28. Success 2

29. Success 3

30. Evolving 1

31. Evolving 2

32. Evolving 3

33. Evolving 4-7 4 6 5 7

34. Evolving 8: Aha! Inverter

35. Evolving – Success 1

39. Merci Danke Sas efharisto Mahalo Merci Dhanyavaad Arigato Vandane Wneeweh Shukran