Nanocomputer Systems Engineering

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Nanocomputer Systems Engineering

• Laying the Key Methodological Foundations for the
  Design of 21st-Century Computer Technology

The full paper is available athttp//www.cise.uf
l.edu/research/revcomp/theory/NanoTech2003/Frank-
NanoTech-2003.doc, .ps.
Michael P. Frank CISE ECE DepartmentsUniversity
of Floridaltmpf_at_cise.ufl.edugt
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Cost-EfficiencyThe Key Figure of Merit

• All practical engineering design-optimization can
  ultimately be reduced to maximization of
  generalized, system-level cost-efficiency.
• Given appropriate models of cost .
• Definition of Cost-Efficiency a Process
  min/actual
• Maximize by minimizing actual
• This is valid even when min is unknown

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Important Cost Categories in Computing
Focus oftraditionaltheories ofso-calledcomput
ationalcomplexity

• Hardware-Proportional Costs
• Initial Manufacturing Cost
• Time-Proportional Costs
• Inconvenience to User Waiting for Result
• (Hardware?Time)-Proportional Costs
• Lifetime-Amortized Manufacturing Cost
• Maintenance Operation Costs
• Opportunity Costs
• Energy-Proportional Costs
• Adiabatic Losses
• Non-adiabatic Losses From Bit Erasure
• Note These may both vary independently of
  (HW?Time)!

These costsneed to beincluded also in
practicaltheoreticalmodels ofnanocomputing
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Two-Pass System Optimization

• A general methodology for the interdisciplinary
  optimization of the design of complex systems.
• Performance characteristicsof system are
  expressed asfunctions of systems design
  parameters, subsystems own characteristics.
• Then, optimize designparameters from top downto
  maximize overall system-wide cost-efficiency.

Top-levelsystems design
High-levelsubsystems
Characterize cost-efficiency from bottom upwards
Optimize design parameters from top downwards.
Mid-levelcomponents
Lowest-leveldesign elements
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Computer Modeling Areas

1. Logic Devices
2. Technology Scaling
3. Interconnections
4. Synchronization
5. Processor Architecture
6. Capacity Scaling

1. Energy Transfer
2. Programming
3. Error Handling
4. Performance
5. Cost

An Optimal, Physically Realistic Model of
Compu-ting Must Accurately Address All these
Areas!
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Fundamental Physical Constraints on Computing
ImpliedUniversal Facts
Affected Quantities in Information Processing
Thoroughly ConfirmedPhysical Theories
Speed-of-LightLimit
Communications Latency
Theory ofRelativity
Information Capacity
UncertaintyPrinciple
Information Bandwidth
Definitionof Energy
Memory Access Times
QuantumTheory
Reversibility
2nd Law ofThermodynamics
Processing Rate
Adiabatic Theorem
Energy Loss per Operation
Gravity
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Landauers Principle (1961)Bit Erasure Creates
Entropy
Before bit erasure
After bit erasure
s0
0
0
s0
Nstates



sN-1
0
0
sN-1
Unitary(1-1)evolution
2Nstates
s0
sN
1
0
Increase in entropy S log 2 k ln
2 Energy lost to heat ST kT ln 2
Nstates



0
sN-1
s2N-1
1
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Reversible / Adiabatic Chips Designed _at_ MIT,
1995-1999
By the author and other then-students in the MIT
Reversible Computing group,under AI/LCS lab
faculty members Tom Knight and Norm Margolus.
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Example Application of Our Engineering
Methodology

• A research question to be answered
• As nanocomputing technology advances,will
  reversible computing become very cost-effective,
  and if so, when?
• We applied our methodology as follows
• Made Realistic Model (Obeying Constraints)
• Optimized Cost-Efficiency in the Model
• Swept Model Parameters over Future Years

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Important Factors Included in Our Model

• Entropic cost of irreversibility
• Algorithmic overheads of reversible logic
• Adiabatic speed vs. energy-loss tradeoff
• Optimized degree of reversibility
• Limited quality factors of real devices
• Communications latencies in parallel algorithms
• Realistic heat flux constraints

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Technology-Independent Model of Nanoscale Logic
Devices

• Id Bits of internal logical state information
  per nano-device
• Siop Entropy generated per irreversible
  nano-device operation
• tic Time per device cycle (irreversible case)
• Sd,t Entropy generated per device per unit
  time (standby rate, from leakage/decay)
• Srop,f Entropy generated per reversible op per
  unit frequency
• ?d Length (pitch) between neighboring
  nanodevices
• SA,t Entropy flux per unit area per unit time

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Technological TrendAssumptions
Entropy generatedper irreversible
bittransition, nats
Absolute thermodynamiclower limit!
Minimum pitch (separation between centers of
adjacent bit-devices), meters.
Nanometer pitch limit
Minimum time perirreversible bit-devicetransitio
n, secs.
Example quantum limit
Minimum cost perbit-device, US.
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Fixed TechnologyAssumptions

• Total cost of manufacture US1,000.00
• User will pay this for a high-performance desktop
  CPU.
• Expected lifetime of hardware 3 years
• After which obsolescence sets in.
• Total power limit 100 Watts
• Any more would burn up your lap. Ouch!
• Power flux limit 100 Watts per square centimeter
• Approximate limit of air-cooling capabilities
• Standby entropy generation rate 1,000
  nat/s/device
• Arbitrarily chosen, but achievable

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Cost-Efficiency Benefits of Reversible Computing
Scenario 1,000/3-years, 100-Watt conventional
computer, vs. reversible computers w. same
capacity.
100,000
1,000
Best-case reversible computing
Bit-operations per US dollar
Worst-case reversible computing
Conventional irreversible computing
All curves would ?0 if leakage not reduced.
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More Recent Work

• Optimizing device size tominimize entropy
  generation

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Minimizing Entropy Generationin Field-Effect
Nano-devices
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Lower Limit to Entropy Generation Per
Bit-Operation

• Scaling withdevices quantumquality factor q.
• The optimal redundancyfactor scales as
  1.1248(ln q)
• The minimumentropy gener-ation scales as q
  -0.9039

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Conclusions

• We have developed an integrated and principled
  methodology for analysis of nanocomputer systems
  engineering.
• Techniques such as this are needed to address
  difficult but important questions.
• E.g., the cost-efficiency of reversible
  computing.
• Preliminary results indicate that reversible
  computing offers extreme cost-efficiency
  advantages for future nanocomputing.
• Even when taking its overheads into account!