1 / 44

Embryological Electronics First NASA/DoD Workshop on Evolvable Hardware

Embryological Electronics First NASA/DoD Workshop on Evolvable Hardware. P. Marchal Centre Suisse d'Electronique et de Microtechnique SA Jaquet-Droz 1 CH-2007 Neuchâtel pierre.marchal@csem.ch http://www.csem.ch. Summary. Introduction to Bio-inspired Systems Embryological Electronics

eryk
Download Presentation

Embryological Electronics First NASA/DoD Workshop on Evolvable Hardware

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Embryological ElectronicsFirst NASA/DoD Workshop onEvolvable Hardware P. Marchal Centre Suisse d'Electronique et de Microtechnique SA Jaquet-Droz 1 CH-2007 Neuchâtel pierre.marchal@csem.ch http://www.csem.ch

  2. Summary • Introduction to Bio-inspired Systems • Embryological Electronics • What is presently available? • Open Avenues for Evolvable Hardware • Conclusion

  3. Introduction to Bio-inspired Systems What is bio-inspiration? Building complex systems Genome-based design

  4. Bio-inspiration? • Nature has acquired a strong experience in complex system design : • 3-billion years of R &D • Powerful constructions (built and maintained) : • longer than hundreds years (animal life) • longer than thousands years (plant life) • Adapting and Evolving solutions: • personal modification is adaptation or learning • inherited modification is evolution

  5. January, the 1st Earth formation March, the 1st Sedimentary rocks May, the 1st First cells : prokaryotes July, the 1st Free oxygen in the air September, the 1st Eukaryotes: differentiated nucleus November, the 19th Cambrian explosion: fossil era December, the 26th Death of dynosaurs At 9:00 pm Homo erectus At 11:45 pm Homo sapiens At 12:00 pm You December, the 31st January, the 1st Y 2 K bug 3-billion years shrinked into 1 year

  6. This is NOT bio-inspiration

  7. Fields of Bio-inspiration evolution healing perceptron Neural nets self- structuration actuators perception sensors Neural nets Genetic algo mechanics VLSI optics Artificial life algorithms

  8. Building Complex Systems 1.- Engineer’s approach 

  9. 0.1mm fertilized egg 1/2 hour, 1 cell 3 hours, 64 cells 6 hours, 10'000 cells Building Complex Systems2.- Nature’s Approach (1)

  10. Building Complex Systems2.- Nature’s Approach (2) MUSCLE CELL LYMPHOCYTES SPERMATOZOON LEUCOCYTE OSTEOCYTE RED CELLS 10 hours, 30'000 cells FIBROPLAST NERVE CELL

  11. Interconnection Part Horizontal Buses Field Programme Functional Vertical Part Buses Field Programmable Gate Arrays

  12. Von Neumann Contribution • He proposed that the production of an automaton by another one should be composed of two phases: • information is once read and copied (transcription) • information is then read and interpreted (translation) • He conceived a self-reproducing automaton

  13. Self-structuring VLSI(genome-based design)

  14. Biodule (biological-like module)

  15. Embryological Electronics Reproduction Adaptation Evolution

  16. No reproduction apparatus

  17. A cell composed of proto-cells • The silicon cell is composed of: • Genome memory • Address computation • Functional cell • Failure handling

  18. Nucleus-like proto-cell • Its function is to: • store the genogram (set of bit-strings - “genes” - that describes the functionality of the silicon cell) • transmit a copy of the genogram to neighbouring cells • boot the address computation

  19. 6 0 0 0 3 0 0 3 = 0 2 = 0 2 5 2 3 0 0 1 2 0 = 3 = 2 1 0 0 4 0 0 0 = 1 3 = 2 1 0 0 0 0 1 0 0 = = 0 2 0 2 0 Storing Process .

  20. 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 Each Nucleus stores its own copy .  6 0 0 0 3 0 0 3 = 0 2 = 0 2 5 2 3 0 0 1 2 0 = 3 = 2 1 0 0 4 0 0 0 = 1 3 = 2 1 0 0 0 0 1 0 0 = = 0 2 0 2 0

  21. Gradient-like control proto-cell • Its function is to: • compute the local address (row & column coordinates) • transmit a copy of the local address to the neighbouring cells • boot the differentiation process (gene expression)

  22. 0 , 1 Local Address Computation

  23. 1,4 2,4 3,4 4,4 1,3 2,3 3,3 4,3 5,3 1,2 2,2 3,2 4,2 5,2 2,1 3,1 4,1 5,1 Continuous Gradient 5,4 0 , 1  1,1

  24. 1,1 2,1 1,1 2,1 1,3 2,3 1,3 2,3 1,3 1,2 2,2 1,2 2,2 1,2 2,1 1,1 2,1 1,1 Repeating Structures 1,1 0 , 1  1,1

  25. Cell Differentiation • the local address is used to pick up, out of the genogram memory, the gene corresponding to that location • the gradient like process enables cell differentiation

  26. 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 1,1 2,1 3,1 1,1 2,1 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 1,3 2,3 3,3 1,3 2,3 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 1,2 2,2 3,2 1,2 2,2 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 23306 00000 22302 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 32040 32000 22000 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 01001 10001 01050 1,1 2,1 3,1 1,1 2,1 Differentiation Process .

  27. Functional Cell • Its function is to: • load the programmable bit-string of the FPGA proto-cell with the local gene • realise a part of the logical function (distributed among the circuit area) • transmit convenient information with the appropriate neighbours

  28. Reset D Q Clock Q Set Family of Cells INTER CONNECTION PART LOCAL GENE FIELD PROGRAMME FUNCTIONAL PART

  29. Immune-like Proto-Cell • Its function is to: • determine the faulty behaviour of a cell, if any, and the severity of the fault • transmit the internal state (faulty or not) to the neighbours • boot the healing phase (restart address computation) if a fault has occurred

  30. 0 6 Healing Process 3 2 3 3 0 6 0 0 0 0 0 2 2 3 0 2 2 3 3 0 0 0 0 0 2 2 3 0 2 3 3 3 3 2 3 2 3 1 3 1 3 2 3 2 0 4 0 3 2 0 0 0 2 2 0 0 0 3 2 0 4 0 3 2 0 0 0 2 2 0 0 0 2 2 2 2 1 2 3 2 1 2 3 2 1 0 1 0 0 1 1 0 0 0 1 0 1 0 5 0 0 1 0 0 1 1 0 0 0 1 0 1 0 5 0 3 1 3 1 2 1 2 1 1 1 1 1 Y 1 2 3 4 5 6 X

  31. 0 6 2 2 3 0 2 2 3 3 0 6 0 0 0 0 0 0 0 0 0 0 3 2 3 3 2 3 2 3 1 3 1 3 3 3 2 2 0 0 0 3 2 0 0 0 3 2 0 4 0 3 2 0 0 0 2 3 2 0 4 0 1 2 1 2 2 2 3 2 2 2 0 1 0 5 0 1 0 0 0 1 1 0 0 0 1 0 1 0 0 1 1 0 1 0 0 1 2 1 2 1 1 1 1 1 3 1 Y 1 2 3 4 5 6 X Healing Process

  32. What is presently available ? A family of self-structuring circuits

  33. MUXTREE (EPFL - 94)  BIODULE 600 DMUXTREE (CSEM - 95)  S.T. HCMOS5 .5m GenomIC (CSEM 96)  MIETEC HCMOS7 .75m MICTREE (EPFL - 97)  BIODULE 602 SRMUX (EPFL - 98)  BIODULE 603 FPOP (CSEM - 98) EM Marin SOI 1m FPPA (CSEM - 99)  TSMC .35m FrameDISC (CSEM - 00)  TSMC .25m Low Medium CELL COMPLEXITY High A family of self-structuring circuits

  34. DMUXTREE

  35. GenomIC

  36. Field Programmable Processor Array (FPPA)

  37. Open Avenues for Evolvable Hardware Applications Adaptation Evolution

  38. Applications • Self-structuring and self-repairing VLSI should be considered in situations where changing and/or repairing is: • too difficult (under sea exploration) • too dangerous (nuclear exposition) • too expensive (deep space exploration) • too risky (human life is in danger) • and functionality should be conserved in presence of defects, radiations or wear out • Emerging applications in automotive (WINS project)

  39. Adaptation • Reconfiguration is based on an event differing from the occurrence of a fault • Physical event adaptation: • swing of power lines • shift in temperature • Informational event adaptation: • change of signal’s bandwidth • object oriented processing

  40. Evolution • Development is based on a description of the structure stored in a genome • Use the genetic algorithm and genetic programming techniques to evolve such systems • Two levels of description may be considered: • high level description  evolution for synthesis • low level description  evolution for adaptation

  41. Conlusion

  42. Parallelism, morphism and adaptation • Massive parallelism: • Multicellular organization • Morphism: • Configurable hardware • Adaptation: • Upgradable software • Reconfigurable hardware

  43. To conclude • We have investigated this research domain • We have acquired the know-how to address a large amount of questions related to fault tolerance as well as evolvable hardware • We have the mastery of the technology • We have patents on it • We are ready to answer any question regarding this field

More Related