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Congestion Estimation in Floorplanning. Supervisor: Evangeline F. Y. YOUNG by Chiu Wing SHAM. Overview. Introduction Background Congestion Modeling Experimental Results Future Works. Introduction. Motivations: 80% of the clock cycle consumed by interconnects

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congestion estimation in floorplanning

Congestion Estimation in Floorplanning

Supervisor:

Evangeline F. Y. YOUNG

by

Chiu Wing SHAM

overview
Overview
  • Introduction
  • Background
  • Congestion Modeling
  • Experimental Results
  • Future Works
introduction
Introduction
  • Motivations:
    • 80% of the clock cycle consumed by interconnects
    • Interconnect optimization becomes the major concern in floorplanning
    • Appropriate interconnect estimation is required in floorplanning
major role of floorplanning
Major Role of Floorplanning
  • Minimization of chip area
  • Optimization of interconnect cost
    • Wirelength
    • Timing delay
    • Routability
  • Others:
    • Heat dissipation
    • Noise reduction
    • Power consumption
congestion planning
Congestion Planning
  • Congestion planning is important to circuit design
    • Excessive congestion may result in a local shortage of routing resources
    • A large expansion in area
    • Failure in achieving timing closure
  • Congestion modeling
    • Given a packing and netlist
    • Estimating the congestion and routability instead of real routing
congestion model a
Congestion Model A

The probability that wire k passing through this grid, Pk(x,y)

=4/6

=0.67

congestion model a1
Congestion Model A

Congestion of the grid (x,y)

- Expected number of wires passing through the grid (x,y), weight(x,y):

limitations
Limitations
  • Model A assumes that all feasible routes have the same probability of being selected
  • In real cases, the routes with less bends should have a higher probability of being selected

The probability that wire k passing through this grid, Pk(x,y)

=8/24

=0.33

congestion model b1
Congestion Model B

where distk(x, y) is the distance from the source of wire k to the grid (x, y) and cntk(r) is the number of grids in the division that is r grids from the source.

Congestion of the grid (x,y) due to wire k

- the probability of wire k pass through the grid (x,y), Pk(x,y):

limitations1
Limitations
  • Routing resources:
    • Both models assume that routing resources are equal at different locations
    • Routing resources should be different at different locations in real cases
  • Wirelength:
    • Both models assume that all nets are routed in their shortest Manhattan distance
    • Some nets may be routed with detours in real cases
our approaches
Our Approaches
  • Congestion Model A*:
    • Based on model A
    • Routing resources can be different at different locations
  • Congestion Model B*:
    • Based on model B
    • Routing resources can be different at different locations
  • Congestion Model C:
    • Based on model B*
    • Routing resources can be different at different locations
    • Each net may be routed with detours
congestion model a2
Congestion Model A*
  • Considering routing resources
congestion model a3
Congestion Model A*
  • Notations:
    • res(x,y): relative routing resources at the grid (x, y)
    • Lk(x,y): the set of feasible routes for wire k passing through the grid (x,y)
    • Lk: the set of all feasible routes for wire k
    • Gk(l): the set of grids that the route l of wire k will pass through
    • wk(l): the weight of each feasible route l
  • Equations:
congestion model b2
Congestion Model B*
  • Considering routing resources
congestion model b3
Congestion Model B*
  • Notations:
    • res(x,y): relative routing resources at grid (x, y)
    • distk(x,y): the distance from the source of wire k to the grid (x,y)
    • divk(r): the set of grids that are r grids from the source of wire k
  • Equation
congestion model c
Congestion Model C
  • Considering routing resources
  • Each net may be routed with detours
congestion model c1
Congestion Model C
  • Notations:
    • res(x,y): relative routing resources at the grid (x, y)
    • dist(x,y): the distance from the the grid (0, 0) to the grid (x,y)
    • divk(r): the set of grids that are r grids from the grid (0,0) of wire k
    • CRk: the set of divisions located in the compulsory region
    • ORk: the set of divisions located in the optional region
    • : degrade factor for the grids outside the SMB region
    • : degrade factor for the grids in the optional region
    • d(i, j, k, l): the distance between the grid (i, j) and (k, l)
congestion model c2
Congestion Model C

Equation:

Compulsory Region (divk(dist(x, y))  CRk):

Optional Region (divk(dist(x, y))  ORk):

implementation
Implementation
  • Floorplanning:
    • Representations: SP
    • Heuristics: Simulated Annealing
    • Cost function: Weighted sum of wirelength and number of over-congested grid
  • Routing
    • Cadence’s WROUTE
future works
Future works
  • Limitations of congestion model C
    • Too many parameters (, ) are used
    • Longer running time
  • Limitations of representation
    • Packed closely together