1. Ontogenetic hardware
Ok, so the Tom Thumb algorithm can self-replicate an arbitrary structure within an FPGA
But what kind of structures is it interesting to self-replicate
And why would you want to do it anyway?

2. Embryonics – Overview
Brief outline:
In this lecture, we will present an overview of the motivations behind the development of the Embryonics project. The overall structure of Embryonic systems will be analysed through a simple example.

3. Ontogenetic hardware Embryonics = embryonic electronics:
Drawing inspiration from growth processes of living organisms to design complex computing systems
Phylogeny (P)
[Evolvability]
PO hw
PE hw
POE hw
Ontogeny (O)
[Scalability]
OE hw
Epigenesis (E)
[Adaptability]

4. Bio-Inspired Approaches
Growth
Self-organization
Massive parallelism (multicellular systems)
Issues that growth can potentially address:
Complexity
Scalability
Fault tolerance

5. Caenorhabditis Elegans
11 December 1998

6. Caenorhabditis Elegans
From S.F. Gilbert, Developmental Biology, Sinauer, 1991

7. Multicellular Organization
959 somatic cells

8. Cellular Differentiation
Pharynx
Intestine

9. Embryonics: How? Iterative electronic circuit based on 3 features:
• multicellular organization
• cellular division
• cellular differentiation

10. Embryonics Landscape Population level (population = S organisms)
Organismic level
(organism = S
cells)
Cellular level
(cell = S
molecules)
Molecular level
(basic FPGA's element)

11. StopWatch

12. StopWatch

13. Multicellular Organization

14. StopWatch

15. StopWatch First step: design of a totipotent cell (stem cell)
(of course, in practice it can be optimized)

16. StopWatch

17. Cellular Differentiation

18. Cloning

19. Cloning

20. Self-Repair

21. BioWatch The application can of course be anything…
But then, the size and structure of the cell will vary from application to application: we need programmable logic!

22. MUXTREE Molecule
The “molecular” layer of Embryonics is an FPGA

23. Cellular Self-Replication
But if we use FPGAs, then we need to CREATE the array of cells in the first place, before differentiation can take place (self-replication)

24. Cellular Self-Replication
But if we use FPGAs, then we need to CREATE the array of cells in the first place, before differentiation can take place (self-replication)

25. Cellular Self-Replication
But if we use FPGAs, then we need to CREATE the array of cells in the first place, before differentiation can take place (self-replication)

26. Cellular Self-Replication
Self-replication will allow the same FPGA partial configuration to be duplicated as many times as needed

27. Cellular Self-Repair
But self-replication, and custom FPGAs, can ALSO be used to improve the reliability of the system

28. Cellular Self-Repair
But self-replication, and custom FPGAs, can ALSO be used to improve the reliability of the system … within limits

29. Operation of the Cell

30. Kill a Molecule

31. Recovered Molecule

32. Kill Again (Kill a Cell)

33. Recovered Cell

34. Implementation - The BioWall

36. Summary
We have seen a basic system implemented using the Embryonics approach. The system exploits self-replication and growth to simplify the layout and to improve reliability
But how do you design this kind of systems?
And can these ideas be applied to real-world circuits and applications?