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Neuromorphic Analog VLSI

Neuromorphic Analog VLSI. David W. Graham West Virginia University Lane Department of Computer Science and Electrical Engineering. Neuromorphic Analog VLSI. Each word has meaning Neuromorphic Analog VLSI. Engineering Versus Biology. Core 2 Duo 65 watts 291 million transistors

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Neuromorphic Analog VLSI

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  1. Neuromorphic Analog VLSI David W. Graham West Virginia University Lane Department of Computer Science and Electrical Engineering

  2. Neuromorphic Analog VLSI Each word has meaning Neuromorphic Analog VLSI

  3. Engineering Versus Biology • Core 2 Duo • 65 watts • 291 million transistors • >200nW/transistor • Brain • 10 watts • >100 billion neurons • ~100pW/neuron

  4. Neuromorphic/Bio-Mimetic Engineering Neuromorphic/Bio-Mimetic Engineering – Using biology to inspire better engineering High-quality processing Low power consumption • Sensorimotor Systems • Intelligent robotics • Intelligent controls • Locomotive systems • Neurons • Systems that learn • Systems that adapt • Neural networks • Understanding biology • Silicon Retina • CMOS imagers • Intelligent imagers • Retinal implants • Audio Systems • Audio front ends • Signal processing systems • Hearing aids • Cochlear implants • Electronic Nose • “Sniff out” odors • Chemical sensors • Drug traffic control • Bio terror detection

  5. Why Neuromorphic Engineering? Interest in exploring neuroscience Interest in building neurally inspired systems Key Advantages • The dynamics is the system • What if our primitive gates were a neuron computation? • a synapse computation? a piece of dendritic cable? • Efficient implementations compute in their memory elements • – more efficient than directly reading all the coefficients • Precise systems out of imprecise parts

  6. Biology and Silicon Devices Similar physics of biological channels and p-n junctions • Drift and Diffusion equations form a built-in Barrier • (Vbi versus Nernst Potential) • Exponential distribution of particles • (Ions in biology and electrons/holes in silicon) Both biological channels and transistors have a gating mechanism that modulates a channel.

  7. Comparison of scales Molecules Channels Synapses Neurons CNS Silicon Parallel Processors Logic Gates Multipliers PIII Transistors 0.1nm 10nm 1mm 0.1mm 1cm 1m

  8. Neuromorphic Products • Neuromorphic Engineering is a relatively young field. However, it is already producing some very popular products. • Logitech Trackball • B.I.O.-Bugs and Robosapien • Neuromorphic Engineering is also helping to advance the field of neuroscience.

  9. Where Can We Go? Smart Embedded Sensors Low-Power Analog • Consumer Electronics • Implantable Devices • Subthreshold Design • Hearing Aids • Cochlear Implants Analog Programmability Powerful Mixed-Signal Systems • Provides digital features to the analog domain • Programmability • Accuracy • Reconfigurability • “Silicon Simulation” Analog alleviates the burden of the digital Bio-Inspired Systems

  10. Why Analog? Much lower power than digital Can perform many computations faster and more efficiently than digital Follows the same physical laws as biological systems

  11. Analog Power Savings G G e e n n e e ' ' s s L L a a w w 1 0 0 W D D S S P P P P o o w w e e r r C C A A D D S S P P P P o o w w e e r r 1 W 1 0 m W P r o g r a m m a b l e Power Dissipated / MMAC A n a l o g P o w e r 0 . 1 m W S a v i n g s > 2 0 Y e a r L e a p 1 W  i n T e c h n o l o g y 1 0 n W 1 9 8 0 1 9 9 0 2 0 0 0 2 0 1 0 2 0 2 0 2 0 3 0 Y e a r • Gene’s Law • Power consumption of integrated circuits decreases exponentially over time • Follows Moore’s Law • Analog computation yields tremendous power savings equal to a >20 year leap in technology • FFT vs. Analog Cochlear Model • 32 subbands at 44.1kHz • FFT consumes ~5mW (audio-streamlined DSP) • Analog consumes <5μW • Analog power savings of >1000

  12. Why VLSI? Cheaper (and easier to mass produce) Smaller Reduces power Keeps everything contained Reduces noise Reduces coupling from the environment Need a large number of transistors to perform real-world computations/tasks Allows a high density or circuit elements (therefore, VLSI reduces costs)

  13. Difference Between Discrete and VLSI Design

  14. To Summarize … Good Things about Analog VLSI Inexpensive Compact Power Efficient Not So Good Things about Analog VLSI (not necessarily bad) Limited to transistors and capacitors (and sometimes resistors if a very good reason) Parasitics and device mismatch are big concerns You are stuck with what you built/fabricated (no swapping parts out) However, Neuromorphic Analog VLSI is all about how to cope with these “problems,” how to get around them, and how to use them as an advantage

  15. Important Considerations We will limit our discussion to CMOS technologies No BJTs Only MOSFETs Therefore, we will discuss only silicon processes

  16. Every story has a beginning… Looking at connections with neurobiology • Begin at MOS device physics • Look at circuits using the device properties • Building small systems from circuits

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