VLSI Physical Design, Springer Verlag

© KLMH
VLSI Physical Design: From Graph Partitioning to Timing Closure
Chapter 1 – Introduction
Original Authors:
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Andrew B. Kahng, Jens Lienig, Igor L. Markov, Jin Hu
1.1
Electronic Design Automation (EDA)
1.2
VLSI Design Flow
1.3
VLSI Design Styles
1.4
Layout Layers and Design Rules
1.5
Physical Design Optimizations
1.6
Algorithms and Complexity
1.7
Graph Theory Terminology
1.8
Common EDA Terminology
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© KLMH
Chapter 1 – Introduction
Electronic Design Automation (EDA)
In 1965, Gordon Moore (Fairchild)
stated that the number of
transistors on an IC would double
every year. 10 years later, he
revised his statement, asserting
that they double every 18 months.
Since then, this “rule” has been
famously known as Moore’s Law.
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Moore’s Law
Moore: „Cramming more components onto integrated circuits"
Electronics, Vol. 38, No. 8, 1965
© KLMH
1.1
Electronic Design Automation (EDA)
© KLMH
1.1
Impact of EDA technologies on
overall IC design productivity and
IC design cost
ITRS 2009 Cost Chart
(in2009
Millions
of Chart
Dollars)
ITRS
Cost
(in Millions of Dollars)
120.0
120.0
120.0
100.0
100.0
100.080.0
80.0
80.060.0
60.0
79.0
79.0
56.479.0
56.4
46.7
46.7
33.646.7
33.6
55.7
55.7
42.5
42.5
31.142.5
31.1
35.2
35.2
46.6
46.6
55.7
40.5
40.5
34.046.6
34.0
40.7
27.2
40.7
29.440.5
27.2
29.4
35.2
29.6
33.6
56.4
29.6
21.4
31.1
34.0
21.4
43.5
40.7
40.020.0
44.9
43.5
20.0
44.9
29.4
39.827.2
36.9
39.8
32.9
32.6
36.9
31.7
29.5
29.6
27.0
26.3 32.9
25.2 32.6 27.0
29.5
23.1 31.7
25.2
20.3 19.4
21.416.9
19.4 26.3
16.9 23.1
15.7 20.3
43.5
15.7
44.9
20.0 0.0
39.8
36.9
0.0
32.9
32.6
31.7
29.5
27.0
25.2
20.3 19.4 26.3
16.9202123.12022 2023 2024
15.7
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
0.0 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
60.040.0
40.0
2010 HW
2011
2012 2013
2014
2015
2016 2017
2019 2020Costs
2021+ ESDA
2022 Tool
2023
2024
Total
Engineering
Costs
+ EDA
EDA
Tool Costs
Costs
Total2018
SW Engineering
Engineering
Costs
Total
HW Engineering
Costs
+
Tool
Total
SW
Costs +
ESDA Tool
Costs
Total HW Engineering Costs + EDA Tool Costs Total SW Engineering Costs + ESDA Tool Costs
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2009
Electronic Design Automation (EDA)
Circuit and Physical Design Process Advancements
1950 -1965
Manual design only.
1965 -1975
Layout editors, e.g., place and route tools, first developed for
printed circuit boards.
1975 -1985
More advanced tools for ICs and PCBs, with more sophisticated
algorithms.
1985 -1990
First performance-driven tools and parallel optimization algorithms
for layout; better understanding of underlying theory (graph theory,
solution complexity, etc.).
1990 -2000
First over-the-cell routing, first 3D and multilayer placement and
routing techniques developed. Automated circuit synthesis and
routability-oriented design become dominant. Start of parallelizing
workloads. Emergence of physical synthesis.
2000 - now
Design for Manufacturability (DFM), optical proximity correction
(OPC), and other techniques emerge at the design-manufacturing
interface. Increased reusability of blocks, including intellectual
property (IP) blocks.
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Time Period
© 2011 Springer Verlag
© KLMH
1.1
VLSI Design Flow
© KLMH
1.2
System Specification
Partitioning
Architectural Design
Functional Design
and Logic Design
Chip Planning
Circuit Design
Placement
Physical Design
Signal Routing
Fabrication
Timing Closure
Packaging and Testing
Chip
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DRC
LVS
ERC
Physical Verification
and Signoff
Clock Tree Synthesis
© 2011 Springer Verlag
ENTITY test is
port a: in bit;
end ENTITY test;
VLSI Design Styles
© KLMH
1.3
Layout editor
Menu Bar
Toolbar
Drawing Tools
Layer Palette
Locator
Cell Browser
Mouse Buttons Bar
Text Windows
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Status Bar
© 2011 Springer
Layout Windows
VLSI Design Styles
© KLMH
1.3
Common digital cells
IN1 IN2
OR
OUT
IN1 IN2
INV
NAND
OUT
IN
OUT
IN1 IN2
NOR
OUT
IN1 IN2
OUT
0
0
0
0
0
0
0
1
0
0
1
0
0
1
1
0
0
1
0
1
1
0
1
0
1
1
0
0
0
1
0
0
1
1
1
0
0
1
1
0
1
0
1
1
1
1
1
1
1
1
1
1
0
1
1
0
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AND
VLSI Design Styles
Vdd
Contact
Metal layer
Vdd
IN2
OUT
IN1
IN1
Poly layer
OUT
Diffusion layer
p-type
transistor
GND
GND
n-type
transistor
OUT
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IN1
IN2
IN2
© KLMH
1.3
VLSI Design Styles
Vdd
Contact
Metal layer
Vdd
IN2
OUT
IN1
IN1
Poly layer
OUT
Diffusion layer
p-type
transistor
GND
GND
n-type
transistor
OUT
Power (Vdd)-Rail
Ground (GND)-Rail
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IN1
IN2
IN2
© KLMH
1.3
VLSI Design Styles
© KLMH
1.3
Standard cell layout with
a feedthrough cell
Power
Pad
Pad
Standard cell layout using
over-the-cell (OTC routing
Standard
Cells
Ground
Pad
Power
Pad
A
Pad
Standard
Cells
Ground
Pad
A
VDD
VDD
GND
A’
GND
Routing
Channel
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Feedthrough
Cell
© 2011 Springer Verlag
A’
VLSI Design Styles
© KLMH
1.3
Layout with macro cells
RAM
PLA
VDD
RAM
PLA
Routing Regions
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Pad
GND
© 2011 Springer Verlag
Standard Cell
Block
VLSI Design Styles
© KLMH
1.3
Field-programmable gate
array (FPGA)
LB
LB
Switchbox
LB
SB
LB
SB
LB
LB
SB
LB
LB
LB
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SB
Connection
© 2011 Springer Verlag
LB
Logic Element
Layout Layers and Design Rules
© KLMH
1.4
Layout layers of an inverter cell
with external connections
Inverter Cell
Vdd
Metal2
Contact
Metal1
Via
polysilicon
External
Connections
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GND
© 2011 Springer Verlag
p/n diffusion
Layout Layers and Design Rules
© KLMH
1.4

Size rules, such as minimum width: The dimensions of any component (shape),
e.g., length of a boundary edge or area of the shape, cannot be smaller than given
minimum values. These values vary across different metal layers.

Separation rules, such as minimum separation: Two shapes, either on the same
layer or on adjacent layers, must be a minimum (rectilinear or Euclidean diagonal)
distance apart.

Overlap rules, such as minimum overlap: Two connected shapes on adjacent layers
must have a certain amount of overlap due to inaccuracy of mask alignment to
previously-made patterns on the wafer.
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Categories of design rules
Layout Layers and Design Rules
© KLMH
1.4
Categories of design rules
: smallest meaningful technologydependent unit of length

a
c
Minimum Width: a
Minimum Separation: b, c, d
e
Minimum Overlap: e
d
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© 2011 Springer Verlag
b
Physical Design Optimizations
© KLMH
1.5

Technology constraints enable fabrication for a specific technology node and are
derived from technology restrictions. Examples include minimum layout widths and
spacing values between layout shapes.

Electrical constraints ensure the desired electrical behavior of the design. Examples
include meeting maximum timing constraints for signal delay and staying below
maximum coupling capacitances.

Geometry (design methodology) constraints are introduced to reduce the overall
complexity of the design process. Examples include the use of preferred wiring
directions during routing, and the placement of standard cells in rows.
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Types of constraints
Algorithms and Complexity
© KLMH
1.6
Runtime complexity

Runtime complexity: the time required by the algorithm to complete as a function of
some natural measure of the problem size, allows comparing the scalability of various
algorithms

Complexity is represented in an asymptotic sense, with respect to the input size n,
using big-Oh notation or O(…)

Runtime t(n) is order f (n), written as t(n) = O(f (n)) when
where k is a real number
n 
t ( n)
k
f ( n)
Example: t(n) = 7n! + n2 + 100, then t(n) = O(n!)
because n! is the fastest growing term as n  .
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
lim
Algorithms and Complexity
© KLMH
1.6
Runtime complexity

Example: Exhaustively Enumerating All Placement Possibilities

Given: n cells

Task: find a single-row placement of n cells with minimum total wirelength by using
exhaustive enumeration.

Solution: The solution space consists of n! placement options. If generating and
evaluating the wirelength of each possible placement solution takes 1 s and
n = 20, the total time needed to find an optimal solution would be 77,147 years!

A number of physical design problems have best-known algorithm complexities that
grow exponentially with n, e.g., O(n!), O(nn), and O(2n).

Many of these problems are NP-hard (NP: non-deterministic polynomial time)

No known algorithms can ensure, in a time-efficient manner, globally optimal solution
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 Heuristic algorithms are used to find near-optimal solutions
Algorithms and Complexity
© KLMH
1.6
Heuristic algorithms

Deterministic: All decisions made by the algorithm are repeatable, i.e., not random.
One example of a deterministic heuristic is Dijkstra’s shortest path algorithm.

Stochastic: Some decisions made by the algorithm are made randomly, e.g., using a
pseudo-random number generator. Thus, two independent runs of the algorithm will
produce two different solutions with high probability. One example of a stochastic
algorithm is simulated annealing.

In terms of structure, a heuristic algorithm can be
 Constructive: The heuristic starts with an initial, incomplete (partial) solution and
adds components until a complete solution is obtained.
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 Iterative: The heuristic starts with a complete solution and repeatedly improves the
current solution until a preset termination criterion is reached.
Algorithms and Complexity
© KLMH
1.6
Heuristic algorithms
Problem Instance
Constructive Algorithm
Initial Solution
Iterative Improvement
Termination
Criterion Met?
no
yes
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Return Best-Seen Solution
Graph Theory Terminology
© KLMH
1.7
Graph
Hypergraph
b
Multigraph
b
b
a
e
f
c
a
a
d
f
c
c
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g
© 2011 Springer Verlag
d
e
Graph Theory Terminology
© KLMH
1.7
Directed graphs with cycles
c
Directed acyclic graph
c
f
f
a
d
e
g
a
b
b
d
g
e
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b
© 2011 Springer Verlag
a
Graph Theory Terminology
© KLMH
1.7
Undirected graph with maximum node degree 3
Directed tree
a
b
a
f
c
b
d
c
g
e
f
g
h
i
j
k
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e
© 2011 Springer Verlag
d
Graph Theory Terminology
© KLMH
1.7
Rectilinear minimum spanning
tree (RMST)
b (2,6)
Rectilinear Steiner minimum
tree (RSMT)
b (2,6)
Steiner point
a (2,1)
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a (2,1)
c (6,4)
© 2011 Springer Verlag
c (6,4)
Common EDA Terminology
© KLMH
1.8
Netlist
b
N3
N2
N4
y
z
N5
c
Pin-Oriented Netlist
(N1: a, x.IN1, y.IN1)
(N2: b, x.IN2, y.IN2)
(N3: x.OUT, z.IN1)
(N4: y.OUT, z.IN2)
(N5: z.OUT, c)
Net-Oriented Netlist
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N1
x
(a: N1)
(b: N2)
(c: N5)
(x: IN1 N1, IN2 N2, OUT N3)
(y: IN1 N1, IN2 N2, OUT N4)
(z: IN1 N3, IN2 N4, OUT N5)
© 2011 Springer
a
Common EDA Terminology
© KLMH
1.8
Connectivity graph
b
N3
N2
N4
z
N5
x
c
z
y
b
c
y
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N1
a
x
© 2011 Springer Verlag
a
Common EDA Terminology
© KLMH
1.8
N1
b
x
N3
N2
N4
y
z
N5
c
b
x
y
z
c
a
0
0
1
1
0
0
b
0
0
1
1
0
0
x
1
1
0
2
1
0
y
1
1
2
0
1
0
z
0
0
1
1
0
1
c
0
0
0
0
1
0
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a
a
© 2011 Springer Verlag
Connectivity matrix
Common EDA Terminology
© KLMH
1.8
Distance metric between two points P1 (x1,y1) and P2 (x2,y2)
d  n x2  x1  y2  y1
n
n
d E ( P1 , P2 )  ( x2  x1 ) 2  ( y2  y1 ) 2
with n = 2: Euclidean distance
d M ( P1 , P2 )  x2  x1  y2  y1
n = 1: Manhattan distance
P1 (2,4)
dM = 7
dE = 5
P2 (6,1)
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dM = 7
© KLMH
Summary of Chapter 1

IC production experienced huge growth since the 1960s
 Exponential decrease in transistor size, cost per transistor, power per transistor, etc

IC design is impossible without simplification and automation
 Row-based standard-cell layout with design rules
 Traditionally, each step in the VLSI design flow has been automated separately by
software (CAD) tools
Software tools use sophisticated algorithms
 Many problems in physical design are NP-hard – solved by heuristic algorithms that
find near-optimal solutions
 Deterministic versus stochastic algorithms
 Constructive algorithms versus iterative improvement
 Graph algorithms – deal with circuit connectivity
 Computational geometry – deal with circuit layout
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

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