“Politehnica” University of Timisoara Course Advisor:  Lucian Prodan Evolvable Systems Web Page:   Teaching  Graduate Courses Summer Semester 2007

What is ACSA ??

Why bother ?? Here are some thoughts…  Computers: Fine exponents of the present days’ technological wave Fine exponents of the present days’ technological wave Solid and trusted performance, indispensable support in many fields Solid and trusted performance, indispensable support in many fields Moore’s law on computer performance still holding (barely?) Moore’s law on computer performance still holding (barely?)  Two major problems (according to Gigascale) Of the small: caused by device shrinking – dominant thus far, industry’s main focus and investment Of the small: caused by device shrinking – dominant thus far, industry’s main focus and investment Of the large: enormity of design verification and manufacturing-test tasks – now a limitation for industrial progress Of the large: enormity of design verification and manufacturing-test tasks – now a limitation for industrial progress

Should we care ?? Here are some more thoughts…  Physical limits of current, conventional technologies approaching fast (also financial limits!) Intel’s 90nm Prescott chip already close to the thermal wall Intel’s 90nm Prescott chip already close to the thermal wall need to individually place atoms inside chips throughout 2010's need to individually place atoms inside chips throughout 2010's  Moore’s law breakdown forecasted around 2018 (source: Intel)  ITRS – two near- and longer-term challenges: sustaining the 17% annual increase in performance sustaining the 17% annual increase in performance developing beyond CMOS materials and applications developing beyond CMOS materials and applications

Who says this ??

Are there any alternatives ?? Emerging Technologies and CMOS Speed Size Cost Switching Energy Source: ITRS report – 2004 update

What about this course ??  New computing architectures: Biologically-inspired computing Biologically-inspired computing –First part of the semester Molecular and DNA computing Molecular and DNA computing Nanoelectronics, … Nanoelectronics, …  New computing paradigms: Quantum computing Quantum computing –Second part of the semester Reversible computing Reversible computing Adiabatic computing, … Adiabatic computing, …

Bioinspired Computing: Why ??  Tradition: engineering and science have developed along separate tracks Natural scientist – a detective: seeking to analyze existing processes, to explain their operation, to model them, and to predict their future behavior Engineer – a builder: tries to create artificial systems (bridges, cars, electronic devices) based on a set of specifications (a description) and a set of primitives (elementary components such as bricks, beams, wires, motors, and transistors)

Bioinspired Computing: Why ?? (2)  Present days: scientists use tools created by engineers engineers allured by certain natural processes   Living organisms – complex systems exhibiting a range of desirable characteristics difficult to realize using traditional engineering methodologies evolution adaptation fault tolerance

Living organisms ??   Living systems characterized by a genetic program (the genome), that guides their development, their functioning, and their death   Considering life on Earth since its very beginning, three levels of organization distinguished: phylogeny ontogeny epigenesis

Phylogeny   First level of organization considered for living systems   Temporal evolution of the genetic program (the genome) concerned   Replication based on genome multiplying – low error rate at individual level   Genetic mechanisms fundamentally nondeterministic –> genetic diversity -> survavibility

Ontogeny   Second level of organization considered for multicellular living systems   Temporal evolution of one individual   Successive cellular division of the zygote -> cellular differentiation   Processes essentially deterministic –> wrong genetic sequence -> notable/lethal malformations

Epigenesis   Third level of organization considered for living systems   Ontogenetic information limited -> another process emerge to integrate knowledge   Example: human brain neurons, connections -> too large to be encoded by the genome   Learning systems – –Nervous – –Endocrine – –Immune

POE Model: How Does Affect US, Computer Engineers ?? -- Phylogeny   Artificial evolution: genetic algorithms, evolution strategies, evolutionary programming, and genetic programming   Large scale programmable circuits: configure function by programming -> FPGAs - three distinct levels of configuration for an FPGA: – –logic –cell interconnection –inputs and outputs  Evolvable hardware: an evolutionary approach to digital design

POE Model: How Does Affect US, Computer Engineers ?? -- Ontogeny   Growth, construction: – –self-test and self-repair – –self-replication – –Embryonics

POE Model: How Does Affect US, Computer Engineers ?? -- Epigenesis   Nervous system: – –Traditionally the most investigated – –Artificial Neural Networks   Immune system: – –software fault detection – –Controllers for mobile robots   Endocrine system – –hormones