A TechnologyIndependent Model for Nanoscale Logic Devices

1
A Technology-Independent Model for Nanoscale
Logic Devices
Michael P. Frank, University of Florida, Depts.
of CISE and ECE,CSE Bldg., Box 116120,
Gainesville, FL 32611, mpf_at_cise.ufl.edu
Reconstructing Physical Quantities in
Computational Terms

• Motivation / problem description
• Candidate nanocomputing technologies operate in a
  wide variety of different physical domains.
• E.g., electronic, mechanical, optical, chemical.
• Even just the all-electronic technologies differ
  by
• Conductivity class
• Semiconductors, conductors, superconductors.
• Operating principles
• Field effect transistors, resonant tunneling
  diodes/transistors, Josephson junctions, etc.
• Confinement dimensions
• Quantum dots, wires, wells.
• Materials
• Metals, silicon crystals, other semiconductors,
  hybrid materials, carbon nanotubes, organic
  molecules,
• Information encoding
• In position, voltage, current, phase, or spin
  states.
• Particles manipulated
• Just electrons, or also holes, ions, dopants,
  nuclei, charged molecules,
• The long-term winner is still completely unclear
• Yet, we would like a theoretical foundation for
  future nanocomputer systems engineering and
  architecture!
• Proposed solution

(Some example implications)

• Fundamental Physical Limits of Computing
• A 100 watt computer expelling its waste heat into
  a room-temperature environment can perform no
  more than
• A single-electron device where electrons may be
  at most 1 volt above their ground state can
  perform no more than
• Any system whose internal computational degrees
  of freedom are at a generalized temperature no
  greater than room temperature can update its
  logical bits at a frequency of no more than
• Device Model Parameters
• Tg Avg. generalized temperature for ops. in the
  coding subsystem.
• Elb Energy per amt. of coding-state info.
  representing 1 logical bit.
• tlbop Elapsed time for carrying out one logical
  bit-operation (transition of a
  logical bit-system).
• td Avg. time btw. decoherence events per bit in
  coding subsystem.
• Plk Leakage power per stored logical bit.
• St Rate of parasitic entopy generation per bit.
• Minimum Entropy Generation per Bit-op

Hierarchical System Design/Optimization
Methodology
wherec Tg/T(overdrivefactor)
whereq td/ttr Tg/Td(quantumqualityfacto
r)
Conclusion The generalized temperature of the
computational degrees of freedom must be gtgt both
the prevailing decoherence thermal temps. in
order to permit ltlt kT energy dissipation per
rev-op.