CMOL vs NASICs T. Wang University of Massachusetts, Amherst September 29, 2005.
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Transcript of CMOL vs NASICs T. Wang University of Massachusetts, Amherst September 29, 2005.
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CMOL vs NASICs
T. WangUniversity of Massachusetts, Amherst
September 29, 2005
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Teng Wang@Umass 2
Agenda
Problems of pure nanoelectronics Problems of Nano-CMOS interface Advantages Problems Conclusions on CMOL
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Teng Wang@Umass 3
Why not Pure Nanoelectronics?
Problems of NanodevicesSimple devices: Limited functionalityComplex devices: Vulnerable to temperatureVoltage gain<1, signal attenuation
Hybrid ArchitectureNanodevices + CMOS circuits Interface between CMOS and nanodevices
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Teng Wang@Umass 4
My Points
• FET has the ability to restore signals
• Our NASICs are also hybrid
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Teng Wang@Umass 5
CMOS/Nano Interface
Stochastic assembling:Limited connectivity
Long time to program
Resistance of interface affects performanceFabrication issue
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Teng Wang@Umass 6
CMOS/Nano Interface in CMOL
α The key idea is to tilt
nanoarray at a certain angle α
Each nanowire can fall on a certain CMOS pin (for addressing)
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Teng Wang@Umass 7
My Points
• sin(a)=Fnano/FCMOS
• cos(a)=n* Fnano/FCMOS
• (Fnano/FCMOS)2+ (n* Fnano/FCMOS)2=1• (Fnano/FCMOS)2=n2+1• Fnano/FCMOS can not be arbitrary.• a must be precisely controlled.• Maybe it can reduce the overhead of
CMOS
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Teng Wang@Umass 8
CMOL Memory Nanodevices for
memory cell CMOS for coding,
decoding, sensing, I/O
Fault tolerance:ReconfigurationHamming codes
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Teng Wang@Umass 9
My Points
• Reconfiguration is an extra assumption.
• How to decide the size of block?
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Teng Wang@Umass 10
Area Efficiency of CMOL Memory
CMOL memory is denser than CMOS memory
Reconfiguration improves fault-tolerance
High yield of single bit is still required.
The area per useful bit as a function ofsingle bit yield, for hybrid and purely
memories.
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Teng Wang@Umass 11
My Points
• The threshhold of acceptable single-bit yield is too high for current nanotechnology
• What’s the yield of total chip?
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Teng Wang@Umass 12
CMOL Logic Circuits
LUT based FPGA: address decoding and sensing require CMOS circuits. For small LUT, CMOS overhead is great.
PLA based FPGA: The same problem as LUT-based FPGA Power dissipation (10KW/cm2)
CMOL FPGA: reconfigurable regular structure
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Teng Wang@Umass 13
My Points
• Why power is so huge?
• Most research indicates that nanodevices consume extremely low power: <10W/cm2
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Teng Wang@Umass 14
CMOL FPGA – A Single Cell
Logics in CMOS Interconnections in
Nanowires
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Teng Wang@Umass 15
My Points
• Density advantage? Logics in CMOS not nano
• How to connect the red/blue terminals with nanowires?
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Teng Wang@Umass 16
CMOL FPGA – A NOR Gate
Wire-OR logic on nanowires?
NOR is enough for arbitrary logic functions
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Teng Wang@Umass 17
My Points
• Does nanowire have wire-OR/AND property?
• 3 CMOS inverter -> a NOR gate? It seems even worse than CMOS.
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Teng Wang@Umass 18
CMOL CrossNets: Neuromorphic Network CrossNet is an architecture of
neuromorphic networkSomas (in CMOS): Neural cell bodiesAxons and dendrites (mutually perpendicular
nanowires)Synapses (switches between nanowires):
control coupling between axons and dendrites
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Teng Wang@Umass 19
Schematic of CrossNet
Light-gray squares in panel (a) show the somatic cells as a whole.
Signs show the somatic amplier input polarities.
Green circles denote nanodevices forming elementary synapses.
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Teng Wang@Umass 20
Conclusions
CMOL for: Memories: reconfiguration, overhead of CMOS FPGAs: really denser than CMOS? Neuromophic networks: no comments
Density, delay, power dissipation Delay should be better than NASIC, since it use a
new layer for CMOS. Power dissipation is hard to compare with NASIC.