Notes
Slide Show
Outline
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CSCI 2570
Introduction to Nanocomputing
  • Errors in Crossbars


  • John E Savage
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Lecture Outline
  • General Properties of nanoarrays


  • NanoFabrics – an early model for nanoarrays


  • NanoPLAS – A programmable architecture


  • Coping with defects
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Technology Forecast
  • DeHon (JETC, Vol. 1, No. 2, 2005) predicts one to two orders magnitude greater density with nanoarrays than FPGAs realized in 22nm lithography, even if latter components are defect-free!
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NW Properties
  • Axially doped NWs
    • Resistance: 0.1MΩ (on) to 10GΩ (off) (>104 ratio)


  • Radially doped NWs
    • Use as shield and control spacing or to encode NW.


  • Silicide – coating Si with Ni and annealing forms metallic NiSi
    • Resistivity of NiSi = 10-5 Ωcm, of Si = 10-3 Ωcm
    • This reduces NW contact resistance to 10KΩ
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Demonstration Project
  • Chen et al. [2003]:


  • Ti/Pt-[2] rotaxane-Ti/Pt sandwich exhibiting state storage with resistance change by > x10
    • From 500KΩ to 9MΩ for 1600nm2 jnctn


  • State switched with +/- 2V, read at +/- 0.2V


  • Molecular sandwich created with Langmuir-Blodgett


  • 8 x 8 crossbar constructed
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Area/Length Comparisons
  • SRAM-based programmable crosspoint has area 2,500λ2 versus 25λ2 for NW crossing [DeHon 1996].


  • NWs can be grown to hundreds of microns in length, but only for large NWs.
    • 10μm x 10μm arrays have been demonstrated
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Defects in Wires and Crosspoints
  • NWs may break during assembly
    • Diameter can be ≈100 atoms
  • Statistical nature of contacts
    • NW-to-MW junctions: small no. of atomic bonds
      • E.g. [Huang 2001]: 95% of contacts good
    • NW-to-NW junctions: composed of 10s of atoms
      • E.g. [Chen 2003]: 85% of crosspoints useable
  • Statistical nature of doping
    • Number of dopants per NW diameter is small
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Defect Models
  • NW Defects
    • Functional: Good contacts at each end, resistance within range, no shorts to other NWs
    • Defective NWs can be found through testing
    • Shells on axial or radial NWs prevent shorts between NWs


  • Crosspoint Defects
    • Programmable (Most common state)
      • Resistance can switched between design limits
    • Non-programmable (More common than shorts)
      • Cannot be turned on – too few molecules at junction
    • Shorted into the on state (treat as defective wires)
      • Cannot be programmed into the off state
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Experimental Demonstrations of Crosspoint Arrays
  • [Chen 2003] 8 × 8 crossbar within a 1 μm2 area, density of 6.4 Gbits cm-2. Two 4 × 4 crossbar subarrays configured to be a nanoscale demultiplexer and multiplexer that were used to read memory bits in a third subarray. Nanoimprint litho used for NWs
  • [Wu 2005] 34 x34 crossbar memory circuits at 30-nm half-pitch nanoimprint lithography used for NWs, LB for film deposition. Read, write, erase and cross-talk were also investigated. Also see [Jung 2004]
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Experimental Demonstrations of Crosspoint Arrays
  • Heath and Stoddart have implemented a 400x400 array of NWs with density of 1011 bits/centimeter.
    • “Modern DRAM circuits have 140nm pitch wires and a memory cell size of 0.0408 mm2.”
    • “Here we describe a 160,000-bit molecular electronic memory circuit, fabricated at a density of 1011 bits cm-2 (pitch 33 nm; memory cell size 0.0011 mm2), that is, roughly analogous to the dimensions of a DRAM circuit projected to be available by 2020.”
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Programmable Wire-OR Plane
  • NWs in black are drawn high by applied voltages
  • Output functions shown


  • Programmed crosspoints realize a routing network
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NW Encoding and Decoding
  • Goal: turn on one NW in each array dimension


  • Earlier lectures describe
    • Undifferentiated NW decoders
      • Random contact decoder
      • Randomized mask-based decoder


    • Differentiated NW decoders
      • Axially encoded NWs
      • Radially encoded NWs
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Signal Restoration and Inversion
  • Wire-OR non-restoring
    • OR is not universal
  • Capacitive coupling of input NW to vertical NW
  • FET at intersection
  • Gives voltage divider
  • Inverter shown at right
  • Reverse Vhigh and Gnd to obtain buffer
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Ideal and Stochastic Restoration Arrays
  • Ideal restoration array has one FET/NW
  • Stochastic assembly raises its ugly head
    • Some NWs may form FETs with multiple vertical NWs
  • How many vertical NWs are needed?
    • A coupon collector problem
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Memory Organization
  • Write
    • Apply voltage across junction
  • Read
    • Disconnect one end of each NW
    • Drive current from a NW in one dimension to NW in other
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Array-Based Architectures
  • Crossbars can be used for storage, computation or routing
  • Amenable to sparing and remapping
  • Challenge:
    • Defect tolerance and avoidance
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Logical Architectures
  • PLA with two programmable and restoration/inversion sections
  • Address discovery followed by programming
  • Two-phase clocking will implement sequential logic
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Interconnection of NanoPLAs
  • Signal routing possible in X- and Y-direction as well as corner turning.
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NanoPLA Block
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Input/Output
  • If NWs connected to CMOS wires, lots of time needed for charge accumulation
  • Better solution: use many identically programmed NWs as collective FET
  • How does one enter multiple independent inputs?
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Defect Tolerance
  • NW sparing
    • Both OR output and restoration NWs must work correctly.
    • If Pw is prob NW is not defective, (Pw)2 is prob that OR output is useable
    • How many NW pairs needed for correct operation?
  • NW failure
    • Pc = prob NW makes good contact on one end
    • Pj = prob no break in NW of length L0.
    • Pctrl = prob NW aligned adequately
  • For NW length L = ρ L0, Pw = (Pc)2 x (Pj)ρ x Pctrl
    • Pw = .8 is typical.
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NW Yield Calculations
  • No. non-defective wired-OR NWs


  • No. uniquely addressable NWs


  • No. non-defective restored NW pairs


  • No. uniquely restored terms



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Defective Programmable Crosspoints
  • Goal: reconfigure to route around defects
  • E.g. OR-term f = A+B+C+E can be assigned to W3 despite defect
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Mapping OR-Terms to Crossbar with Defects
  • This is a matching problem.
    • Fig (a) shows defects
    • Fig (b): NWs to which OR terms can be mapped
      • f1 = a+b+c+d, f2 = a+c+e, f3 = b+c, f4 = d+e
    • Fig (c): A matching
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Imperfect NW Control
  • Our binary model is accurate if each MW provides good control.
  • Realistically, some MWs may only partially turn off some NWs.
  • Also, some MWs may occasionally fail to control some NWs.
  • Our decoders must be fault-tolerant!
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Ideal Decoders with Errors
  • To apply the ideal model to real-world decoders, consider binary codewords with random errors.
  • If cij = e, the jth MW increases ni‘s resistance by an unknown amount.
  • Consider input A such that the jth MW carries a field. A functions reliably if a MW for which cik = 1 carries a field.
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Balanced Hamming Distance
  • Consider two error-free codewords, ca and cb. Let |ca - cb] denote the number of inputs for which caj = 1 and cbj = 0.
  • The balanced Hamming distance (BHD) between ca and cb is 2•min(|ca - cb], |cb - ca]).
  • If ca and cb have a BHD of 2d + 2 they can collectively tolerate up to d errors.
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Fault-Tolerant Random Particle Decoders
  • In a randomized-contact decoder, cij = 1 with some fixed probability, p.
  • If each pair of codeword has a BHD of at least 2d + 2, the decoder can tolerate d errors per pair.
  • This holds with probability > 1- f  when