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A New Effective Congestion Model in Floorplan Design

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Title: A New Effective Congestion Model in Floorplan Design


1
A New Effective Congestion Model in Floorplan
Design
  • Yi-Lin Hsieh and Tsai-Ming Hsieh
  • Department of Information and Computer
    Engineering
  • Chung Yuan Christian University
  • Chung-Li, Taiwan, R.O.C.
  • DATE 04
  • Feb. 19 , 2004

2
Outline
  • Introduction
  • Problem Formulation
  • Probabilistic Analysis
  • Motivation
  • Irregular-Grid Congestion Model
  • Experimental results
  • Conclusion

3
Introduction
  • Floorplanning in physical design
  • Problem
  • Given a set of modules, find a non-overlapping
    placement of modules
  • Expressions and algorithms
  • Normalized Polish expression, sequence pair,
    Btree, , etc.
  • Simulated annealing algorithm, genetic algorithm,
    simulated tempering algorithm, , etc.

4
Introduction(cont.)
  • Objectives
  • Minimize
  • Area
  • Total interconnection length
  • Wire congestion
  • Delay
  • With constraints
  • Boundary
  • Alignment and abutment
  • Frame shape

5
Introduction
Introduction(cont.)
  • Wire congestion
  • Influence
  • Decrease the performance of circuits
  • Cause an unroutable design
  • Affect timing constraint and delay constraint
  • Congestion model for estimation
  • Accuracy - correspond to the post-route result
  • Efficiency - be embedded in iterative algorithms

6
Problem Formulation
  • Input
  • Areas and aspect ratios of m soft modules M1, M2,
    , Mm
  • Netlist of n nets N1, N2, , Nn
  • Output
  • A legal floorplan which achieves some
    optimization objects
  • Objectives
  • Minimize the area of floorplan
  • Minimize the interconnection length
  • Minimize the estimated cost of wire congestion
  • Major work
  • Propose a new effective congestion model to
    estimate the congestion of a floorplan solution

7
Problem Formulation(cont.)
  • Beforehand specification
  • Floorplanning methodology
  • Normalized Polish expression
  • Simulated annealing algorithm
  • Determination of pin locations
  • Intersection-to-intersection
  • Multi-pin net
  • Divided into 2-pin nets by minimum spanning tree

8
Problem Formulation(cont.)
  • Assumption of routing
  • Routing with Manhattan distance
  • Definition
  • The region which may be passed through by a net
    is
  • A point -
  • ignored
  • A line -
  • excluded from our computing formulas
  • A rectangular range -
  • called the routing range of the net

9
Problem Formulation(cont.)
  • Type of a net
  • Type I
  • One pin p1i is lower-left to the other pin p2i
  • Type II
  • One pin p1i is upper-left to the other pin p2i

10
Probabilistic Analysis
  • Proposed by
  • J. Lou et al.(16ISPD 2001) originally in
    placement
  • C. W. Sham et al.(25ISPD 2002) in floorplanning
  • Estimating steps
  • Divide a floorplan solution into 2-D array with
    fixed-size grids

11
Probabilistic Analysis (cont.)
  • Compute the routes for a net passing through a
    grid
  • Example

12
Probabilistic Analysis (cont.)
  • Assume Ni covers g1i g2i grids. Assign the most
    lower-left grid to be (0, 0). For a grid at (x,
    y) where
  • 0 ? x lt g1i and 0 ? y lt g2i , we define Tai(x, y)
    to be the number of routes starting from the grid
    including p1i (lower-left) to (x,y),
  • and Tbi(x, y) to be the number of routes starting
    from the grid including p2i (upper-left) to
    (x,y).
  • Tai(x, y) Tbi(x, y) is the number of routes for
    a net
  • passing through a grid at (x, y)
  • Tbi(x, y) Tai(g1i 1 x, g2i 1 y)

(g1i-1, g2i-1)
g2i
(x, y)
(0, 0)
g1i
13
Probabilistic Analysis (cont.)
  • Compute the probability for a net passing through
    a grid
  • For a Type 1 net
  • The number of total routes is Tai(g1i 1, g2i
    1)
  • The probability for Ni passing through a grid at
  • (x, y) is

14
Probabilistic Analysis (cont.)
  • Process all the nets and obtain the summation of
    probabilities for passing through a grid to be
    the congestion cost of that grid
  • Use the average cost of the top 10 most
    congested grids to be the congestion cost of the
    floorplan solution
  • Time complexity O(n G1 G2)
  • n the number of nets
  • G1 G2 the partitioning grids of the floorplan

15
Motivation
  • Weakness of previous model
  • The number of fixed-size grids affects the
    accuracy greatly
  • The number of fixed-size grids is completely
    determined by users

16
Motivation (cont.)
  • Waste time on estimating the meaningless and less
    congested regions

17
Motivation (cont.)
  • Observation
  • The way to partition estimating grids is
    important to a congestion model
  • The information provided by nets is related to
    the condition of wire congestion
  • Our new congestion model
  • According to the routing ranges
    of nets to divide the floorplan
  • Provide a more accurate and
    rapid congestion model

18
Irregular-GridCongestion Model
  • Overview
  • Introduction to Irregular-Grid and our estimating
    steps
  • The computation of the probability for a net
    passing through an IR-grid
  • Accurate approximating formulas for the
    computation of the probabilities
  • Analysis of the accuracy of the approximating
    formulas
  • The summary of the characteristics and
    excellences in our Irregular-Grid congestion model

19
Irregular-GridCongestion Model (cont.)
  • Irregular-Grid
  • Partitioned by routing ranges of nets
  • IR-grid
    The partitioned rectangular grids
    with irregular sizes
  • Each pin will be always on the partitioning lines
  • Each net will pass through several IR-grids

20
Irregular-GridCongestion Model (cont.)
  • The congestion cost of an IR-grid is related to
  • The summation of the probabilities for all nets
    passing through the IR-grid
  • The size of the IR-grid
  • Estimating steps
  • 1) Divide a floorplan solution into
    Irregular-grid
  • with IR-grids
  • 2) Compute the routes for a net passing through
  • an IR-grid
  • 3) Compute the probability for a net passing
  • through an IR-grid

21
Irregular-GridCongestion Model (cont.)
  • 4) Process all the nets and obtain the summation
    of
  • probabilities for all nets passing through a
    grid
  • 5) The congestion cost of a unit area in an
    IR-grid is
  • determine by
  • sum of probabilities for all nets
    passing through the IR-grid
  • the size of the
    IR-grid
  • 6) Use the average cost of the top 10 most
  • congested unit area to be the congestion cost
    of
  • the floorplan solution

22
Irregular-GridCongestion Model (cont.)
  • Compute the routes for a net passing through an
    IR-grid
  • Example
  • The number of routes passing through the IR-grid
    is (5x115x1)(4x510x420x3)(35x3) 245

23
Irregular-GridCongestion Model (cont.)
  • There exists an IR-grid I in the routing range
    of Ni. The lower-left corner is at (x1I, y1I) and
    the upper-right corner is at (x2I, y2I)
  • Ni is Type I
  • the probability for Ni passing through I is
  • Ni is Type II
  • the probability for Ni passing through I is

24
Irregular-GridCongestion Model (cont.)
  • Accurate approximating formulas
  • Goal
  • Find an accurate approximating formula to the
    probability formula for a net passing through an
    IR-grid, and
  • make the time complexity of the computation be
    constant time
  • Inducing process
  • For a Type I net Ni

25
Irregular-GridCongestion Model (cont.)
Original formula gtgt Hypergeometric Distribution
26
Irregular-GridCongestion Model (cont.)
Hypergeometric Distribution gtgt Normal
Distribution
27
Irregular-GridCongestion Model (cont.)
The definite integral can be easily calculated
by Simpsons rule of integration in constant
time.
28
Irregular-GridCongestion Model (cont.)
  • Analysis of accuracy and modification
  • Accuracy of approximating formulas
  • Observation

29
Irregular-GridCongestion Model (cont.)
  • Advantages
  • Provide a unified basis to partition estimated
    region
  • Reduce the dependence between the number of grids
    and accuracy
  • Reduce the run time and increase the accuracy
  • Induce effective approximating formulas and make
    the time complexity of the computation be
    constant time
  • Total time complexity is O(n3) O(n G1 G2)

30
Experiment results
  • Platform
  • Pentium IV 2.4GHz PC with 256 RAM
  • Microsoft Windows XP
  • Microsoft Visual C 6.0
  • MCNC Benchmarks

31
Experiment results (cont.)
  • Experiment I
  • Improvement of congestion

Optimize area and wire length only VS
Optimize area, wire length and congestion with
Irregular-Grid model
Comparison results
32
Experiment results (cont.)
  • Experiment II
  • Covergency of congestion costs in SA
  • process (ami 33)
  • A IR-grid
  • B 10 10 µm2
  • fixed grid
  • C 50 50 µm2
  • fixed grid

33
Experiment results (cont.)
  • Experiment III Run time(ami33)

Optimize congestion only with Irregular-Grid model
Optimize congestion only with Fixed-grid model
34
Conclusion
  • We propose a concept of irregular-grid to build
    up a new effective congestion model in
    flooplanning design.
  • Our new model could estimate congestion of a
    floorplan more accurately in less run time and
    could be embedded into a floorplanner.
  • Three experimental results validate our
    theoretical work and our model performs well in
    congestion estimating of floorplans.
  • In the future, we want to test the results of our
    model by a real global router to verify the
    practical efficiency.

35
  • Thank You !
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