nanoscale digital computation through percolation mustafa altun electrical and computer engineering...
TRANSCRIPT
Nanoscale Digital Computation Through
Percolation
Mustafa AltunMustafa Altun
Electrical and Computer Engineering
DAC, “Wild and Crazy Ideas” Session ─ San Francisco, July 29, 2009
University of Minnesota
Non-Linearities
22
From vacuum tubes, to transistors, to carbon nanotubes, the basis of digital computation is a robust non-linearity.
signal in
sig
nal out
Holy Grail
Randomness at the Nanoscale
33
Probabilistic FET-like connections in a stochastically assembled nanowire array.
Self-assembled topologies. High density of bits/
logic/interconnects. High defect and failure rates. Inherent randomness in
both interconnects and signal values.
General Characteristics of Nanoscale Circuits:
Nanoscale Computation through Percolation
Given: Physical structures exhibiting randomness.
Want: Robust digital computation.
“WACI” idea: Exploit the mathematics of percolation.
Percolation TheoryRich mathematical topic that forms the basis of explanations of physical phenomena such as diffusion and phase changes in materials.
Sharp non-linearity in global
connectivity as a function of random local connectivity.
RandomGraphs
Broadbent & Hammersley (1957); Kesten (1982); and Grimmett (1999).
0 .0 0 .2 0 .4 0 .6 0 .8 1 .0
P ro b a b ility o f lo ca l co n n ectiv ity
0 .0
0 .2
0 .4
0 .6
0 .8
1 .0P
roba
bilit
y of
glo
bal c
onne
ctiv
ity
Percolation Theory
66
Poisson distribution of points with density λPoints are connected if their distance is less than 2r
Study probabilityof connected components
S
D
Percolation Theory
There is a phase transition at a critical node density value.
8888
Nanowire crossbar arrays
Suppose that, in this technology, crosspoints are FET-like junctions.
When a high or low voltage is applied, these develop low or high impedances, respectively.
METAL INSULATOR
TOP
LEFT RIGHT
BOTTOM
V-Applied
signal out
sig
nal in
9999
Crosspoints as squares
We model each crosspoint as a square. (Black corresponds to ON; white corresponds to OFF.)
10101010
Implementing Boolean functions
TOP
C Columns
LE
FT
RIG
HTR
Row
s
f (X
11,…
,XR
C)
g (X11,…,XRC)
N R
ows
M Columns
INSULATORV-applied (Xij)
BOTTOM
X11
XRCXR1
X12 X1C
XR2
X(R-1)1
X21
X1(C-1)
X2C
X(R-1)C
XR(C-1)
signals in: Xij’ssignals out: connectivity top-to-bottom / left-to-right.
1111
An example with 16 Boolean inputs
1111
A path exists between top and bottom, f = 1
RIG
HT
TOP
BOTTOM
LE
FT
0
0 1
1
1 0
00
1
1
1
1 0
1
00
RIG
HT
TOP
BOTTOML
EF
T
12121212
An example on 2×2 array
Relation between p1 ─ probability of experiencing ON crosspoint ─ and switch’s behavior.
If p1 is 0.9 then the switch is ON with probability 95%. (The probability of getting an error is 5%.)
If p1 is 0.1, the switch is OFF with probability 95%. (The probability of getting an error is 5%.)
BOTTOM
TOP
LE
FT
RIG
HT
BOTTOM
TOP
LE
FT
RIG
HT
BOTTOM
TOP
LE
FT
RIG
HT
BOTTOM
TOP
LE
FT
RIG
HT
p14 4p1
3(1-p1) 4p1(1-p1)3 (1-p1)
4 p1=0.9 0.66 0.29 3.6e-3 1e-4 p1=0.1 1e-4 3.6e-3 0.29 0.66
13131313
Non-Linearity Through Percolation
p2 versus p1 for 1×1, 2×2, 6×6, 24×24, 120×120, and infinite size
lattices.
TOP
BOTTOM
Each square in the lattice is colored black with
independent probability p1.
p2 is the probability that a connected path
exists between the top and bottom plates.
0 .0 0 .2 0 .4 0 .6 0 .8 1 .0
0 .0
0 .2
0 .4
0 .6
0 .8
1 .0
pc
p1p 2
14141414
Defects matter!
Ideally, if the applied voltage is 0, then all the crosspoints are OFF and so there is no connection between any of the plates.
Ideally, If the applied voltage is VDD, then all the crosspoints are ON and so the plates are connected.
With defect in nanowires, not all crosspoints will respond this way.
TOP
BOTTOM
BOTTOM
TOP
RIG
HTL
EF
TL
EF
T
Ideal case
BOTTOM
TOPR
IGH
TLE
FT
TOP
BOTTOM
RIG
HTL
EF
T
Real case
Real case
V-Applied
Ideal case
RIG
HT
DEFECT
1515
Margins
1515
One-margin: Tolerable p1 ranges for which we interpret p2 as logical one.
Zero-margin: Tolerable p1 ranges for which we interpret p2 as logical zero.
Margins correlate with the degree of defect tolerance.
0 .0 0 .2 0 .4 0 .6 0 .8 1 .0 - P ro b a b ility o f lo ca l co n n ectiv ity
0 .0
0 .2
0 .4
0 .6
0 .8
1 .0
-
Pro
babi
lity
of g
loba
l con
nect
ivit
y
Z E R O -M A R G IN
p1
p2
O N E - M A R G IN
1616
Margin performance with a 2×2 lattice
1616
f =X11X21+X12X22
g =X11X12+X21X22
Different assignments of input variables to the regions of the network affect the margins.
LE
FT
RIG
HT
BOTTOM
TOP
X12X11
X22X21
X11 X21 X12 X22 f Margin g Margin
0 0 0 0 0 40% 0 40%
0 0 0 1 0 25% 0 25%
0 0 1 1 1 14% 0 23%
0 1 0 1 0 23% 1 14%
0 1 1 0 0 0% 0 0%
0 1 1 1 1 14% 1 14%
1 1 1 1 1 25% 1 25%
1717
One-margins (always good)
1717
Defect probabilities exceeding the one-margin would likely cause an (1→0) error.
LE
FT
RIG
HT
BOTTOM
TOP
1
0 1
0
f =1f =00 .0 0 .2 0 .4 0 .6 0 .8 1 .0
- P ro b a b ility o f lo ca l co n n ectiv ity
0 .0
0 .2
0 .4
0 .6
0 .8
1 .0
-
Pro
babi
lity
of g
loba
l con
nect
ivit
y
p1
p2
ONE-MARGIN
1818
Good zero-margins
1818
Defect probabilities exceeding zero-margin would likely cause an (0→1) error.
LE
FT
RIG
HT
BOTTOM
TOP
0
1 1
0
f =0f =10 .0 0 .2 0 .4 0 .6 0 .8 1 .0
- P ro b a b ility o f lo ca l co n n ectiv ity
0 .0
0 .2
0 .4
0 .6
0 .8
1 .0
-
Pro
babi
lity
of g
loba
l con
nect
ivit
y
p1
p2
ZERO-MARGIN
1919
Poor zero-margins
1919
Assignments that evaluate to 0 but have diagonally adjacent assignments of blocks of 1's result in poor zero-margins
LE
FT
RIG
HT
BOTTOM
TOP
1
1 0
0
f =0f =10 .0 0 .2 0 .4 0 .6 0 .8 1 .0
- P ro b a b ility o f lo ca l co n n ectiv ity
0 .0
0 .2
0 .4
0 .6
0 .8
1 .0
-
Pro
babi
lity
of g
loba
l con
nect
ivit
y
p1
p2
POOR ZERO-MARGIN
2020
Lattice duality
Note that each side-to-side connected path corresponds to the AND of the inputs; the paths taken together correspond to the OR of these AND terms, so implement a sum-of-products expression.
A necessary and sufficient condition for good error margins is that the Boolean functions corresponding to the top-to-bottom and left-to-right plate connectivities f and g are dual functions.
TOP
C Columns
LE
FT
RIG
HTR
Row
s
f (X
11,…
,XR
C)
g (X11,…,XRC)
BOTTOM
X11
XRCXR1
X12 X1C
XR2
X(R-1)1
X21
X1(C-1)
X2C
X(R-1)C
XR(C-1)
2121
Lattice duality
LE
FT
RIG
HT
BOTTOM
TOP
RIG
HTL
EF
TBOTTOM
TOP
0
0 1
0
0 1
01
1
1
0
1 1
1
11
0
10
0
00
0 1
0
1
1
10
0
1 0
),.....,(),.....,( 1111 rcrcD XXgXXfgf
2222
Further work Solve the logic synthesis problem.
(Bring continuum mathematics into the field.)
Explore physical implementation in nanowire arrays.
Explore percolation as a model for digital computation with DNA and other molecular substrates.
Funding
2323
NSF CAREER Award #0845650
MARCO (SRC/DoD) Contract #NT-1107