% Boyd, Kim, Patil, and Horowitz, "Digital circuit optimization
% via geometric programming"
% Written for CVX by Almir Mutapcic 02/08/06
%
% We consider a chain of N inverters driving a load capacitance CL.
% The problem is to find optimal scale factors for the inverter
% that minimize the sum of them (area), while obeying constraints
% on the maximum delay through the circuit, and minimum and maximum
% limits on scale factors. There are no limits on the total power.
% (For more details about the inverter chain see sec. 2.1.11 in the paper.)
%
%   minimize   sum(x)
%       s.t.   T_j <= Dmax          for j an output gate
%              T_j + d_i <= T_i     for j in FI(i)
%              x_min <= x <= x_max
%
% where variables are x and T.
% Here we use data structures and digital circuit models from the
% referenced paper.

%********************************************************************
% problem data
%********************************************************************
N  = 8;      % number of inverters
CL = 20;     % capacitance load
Dmax = 20;   % maximum delay through the circuit
x_min = 1;   % minimum scale factor
x_max = 20;  % maximum scale factor

% circuit labeling convention:
% label primary input (input to the first inverter in the chain) with N+1
% label primary output (output of the last inverter in the chain) with N+2
% label inverters in the chain with 1,2,...,N based on their location

% primary input and primary output labels (start with N+1)
primary_inputs  = [N+1];
primary_outputs = [N+2];
M = N + length( primary_inputs ) + length( primary_outputs );

% fan-in cell array for a straight chain of inverters
FI{1} = [N+1];   % fan-in of the first inverter is the primary input
for k = 2:N
  FI{k} = [k-1]; % fan-in of other inverters is the inverter feeding into them
end
FI{N+2} = [N];   % fan-in of the primary output is the last inverter in the chain

% fan-out cell array
% (will be computed from the fan-in cell array, no need to modify)
FO = cell(M,1);
for gate = [1:N primary_outputs]
  preds = FI{gate};
  for k = 1:length(preds)
    FO{preds(k)}(end+1) = gate;
  end
end

% input and internal capacitance of gates and the driving resistance
Cin_norm  = ones(N,1);
Cint_norm = ones(N,1);
Rdrv_norm = ones(N,1);

% place extra capacitance before the input of the 5th inverter
Cin_norm(5) = 80;

% primary output has Cin capacitance (but has no Cload)
Cin_po = sparse(M,1);
Cin_po(primary_outputs) = CL;

% primary input has Cload capacitance (but has no Cin)
Cload_pi = sparse(M,1);
Cload_pi(primary_inputs) = 1;

%********************************************************************
% optimization
%********************************************************************
cvx_begin gp
  % optimization variables
  variable x(N)                 % sizes
  variable T(N)                 % arrival times

  % minimize the sum of scale factors subject to above constraints
  minimize( sum(x) )
  subject to

    % input capacitance is an affine function of sizes
    Cin  = Cin_norm.*x;
    Cint = Cint_norm.*x;

    % driving resistance is inversily proportional to sizes
    R = Rdrv_norm./x;

    % gate delay is the product of its driving resistance and load cap.
    Cload = cvx( zeros(N,1) );
    for gate = 1:N
      if ~ismember( FO{gate}, primary_outputs )
        Cload(gate) = sum( Cin(FO{gate}) );
      else
        Cload(gate) = Cin_po( FO{gate} );
      end
    end

    % delay
    D = 0.69*ones(N,1).*R.*( Cint + Cload );

    % create timing constraints
    for gate = 1:N
      if ~ismember( FI{gate}, primary_inputs )
        for j = FI{gate}
          % enforce T_j + D_j <= T_i over all gates j that drive i
          D(gate) + T(j) <= T(gate);
        end
      else
        % enforce D_i <= T_i for gates i connected to primary inputs
        D(gate) <= T(gate);
      end
    end

    % circuit delay is the max of arrival times for output gates
    output_gates = [FI{primary_outputs}];
    circuit_delay = max( T(output_gates) );

    % collect all the constraints
    circuit_delay <= Dmax;
    x_min <= x <= x_max;
cvx_end

% message about extra capacitance and result display
disp(' ')
disp(['Note: there is an extra capacitance between the 4th and 5th inverter'...
     ' in the chain.'])
fprintf(1,'\nOptimal scale factors are: \n'), x

% plot scale factors and maximum delay for inverter i
close all;
subplot(2,1,1); plot([1:N],T,'g--',[1:N],T,'bo');
ylabel('maximum delay T')
subplot(2,1,2); stem([1:N],x);
ylabel('scale factor x')
xlabel('inverter stage')

 
Calling Mosek 9.1.9: 154 variables, 69 equality constraints
   For improved efficiency, Mosek is solving the dual problem.
------------------------------------------------------------

MOSEK Version 9.1.9 (Build date: 2019-11-21 11:32:15)
Copyright (c) MOSEK ApS, Denmark. WWW: mosek.com
Platform: MACOSX/64-X86

Problem
  Name                   :                 
  Objective sense        : min             
  Type                   : CONIC (conic optimization problem)
  Constraints            : 69              
  Cones                  : 38              
  Scalar variables       : 154             
  Matrix variables       : 0               
  Integer variables      : 0               

Optimizer started.
Presolve started.
Linear dependency checker started.
Linear dependency checker terminated.
Eliminator started.
Freed constraints in eliminator : 14
Eliminator terminated.
Eliminator started.
Freed constraints in eliminator : 0
Eliminator terminated.
Eliminator - tries                  : 2                 time                   : 0.00            
Lin. dep.  - tries                  : 1                 time                   : 0.00            
Lin. dep.  - number                 : 0               
Presolve terminated. Time: 0.00    
Problem
  Name                   :                 
  Objective sense        : min             
  Type                   : CONIC (conic optimization problem)
  Constraints            : 69              
  Cones                  : 38              
  Scalar variables       : 154             
  Matrix variables       : 0               
  Integer variables      : 0               

Optimizer  - threads                : 8               
Optimizer  - solved problem         : the primal      
Optimizer  - Constraints            : 46
Optimizer  - Cones                  : 38
Optimizer  - Scalar variables       : 131               conic                  : 114             
Optimizer  - Semi-definite variables: 0                 scalarized             : 0               
Factor     - setup time             : 0.00              dense det. time        : 0.00            
Factor     - ML order time          : 0.00              GP order time          : 0.00            
Factor     - nonzeros before factor : 177               after factor           : 238             
Factor     - dense dim.             : 0                 flops                  : 3.09e+03        
ITE PFEAS    DFEAS    GFEAS    PRSTATUS   POBJ              DOBJ              MU       TIME  
0   5.4e+00  5.2e+00  4.1e+01  0.00e+00   4.033019593e+01   0.000000000e+00   1.0e+00  0.00  
1   1.2e+00  1.1e+00  5.9e+00  2.62e-01   9.270759647e+00   -2.725524360e+00  2.1e-01  0.01  
2   4.2e-01  4.0e-01  1.3e+00  8.24e-01   1.384257477e+00   -3.217225105e+00  7.7e-02  0.01  
3   8.5e-02  8.1e-02  1.3e-01  9.02e-01   -2.262952577e+00  -3.255934733e+00  1.6e-02  0.01  
4   3.6e-02  3.4e-02  3.9e-02  8.67e-01   -2.964826722e+00  -3.413739959e+00  6.6e-03  0.01  
5   5.2e-03  4.9e-03  2.0e-03  9.75e-01   -3.420308403e+00  -3.485113953e+00  9.5e-04  0.01  
6   7.7e-04  7.3e-04  1.2e-04  1.02e+00   -3.465104112e+00  -3.474613264e+00  1.4e-04  0.01  
7   2.5e-05  2.4e-05  6.6e-07  1.01e+00   -3.473222385e+00  -3.473528037e+00  4.5e-06  0.01  
8   3.8e-07  3.6e-07  1.3e-09  1.00e+00   -3.473499452e+00  -3.473504164e+00  7.0e-08  0.01  
9   1.2e-08  1.1e-08  6.8e-12  1.00e+00   -3.473504932e+00  -3.473505078e+00  2.1e-09  0.01  
10  2.4e-08  1.0e-08  5.8e-12  3.92e-01   -3.473504942e+00  -3.473505074e+00  1.9e-09  0.01  
11  1.8e-08  9.6e-09  5.4e-12  1.91e+00   -3.473504974e+00  -3.473505098e+00  1.9e-09  0.01  
12  2.5e-08  8.7e-09  4.7e-12  1.01e+00   -3.473504991e+00  -3.473505104e+00  1.7e-09  0.02  
13  2.5e-08  8.6e-09  4.6e-12  1.01e+00   -3.473504994e+00  -3.473505105e+00  1.7e-09  0.02  
14  2.5e-08  8.6e-09  4.6e-12  3.10e+00   -3.473504994e+00  -3.473505105e+00  1.7e-09  0.02  
15  2.6e-08  8.5e-09  4.6e-12  1.02e+00   -3.473504994e+00  -3.473505105e+00  1.7e-09  0.02  
16  2.6e-08  8.4e-09  4.5e-12  1.00e+00   -3.473504996e+00  -3.473505106e+00  1.6e-09  0.02  
17  2.6e-08  8.4e-09  4.5e-12  1.67e+00   -3.473504997e+00  -3.473505106e+00  1.6e-09  0.02  
18  1.6e-08  7.6e-09  3.8e-12  7.48e-01   -3.473505006e+00  -3.473505104e+00  1.5e-09  0.02  
19  2.2e-08  7.6e-09  3.8e-12  7.63e-01   -3.473505006e+00  -3.473505104e+00  1.5e-09  0.02  
20  2.4e-08  7.3e-09  3.5e-12  1.00e+00   -3.473505013e+00  -3.473505106e+00  1.4e-09  0.02  
21  1.9e-08  6.9e-09  3.2e-12  1.00e+00   -3.473505021e+00  -3.473505109e+00  1.3e-09  0.02  
22  2.3e-08  6.8e-09  3.2e-12  1.00e+00   -3.473505023e+00  -3.473505110e+00  1.3e-09  0.02  
23  2.6e-08  6.7e-09  3.2e-12  1.02e+00   -3.473505023e+00  -3.473505110e+00  1.3e-09  0.02  
24  2.6e-08  6.7e-09  3.1e-12  1.00e+00   -3.473505024e+00  -3.473505111e+00  1.3e-09  0.03  
25  2.6e-08  6.6e-09  3.0e-12  7.25e-01   -3.473505026e+00  -3.473505110e+00  1.3e-09  0.03  
26  2.7e-08  6.5e-09  3.0e-12  1.01e+00   -3.473505027e+00  -3.473505111e+00  1.2e-09  0.03  
27  2.7e-08  6.5e-09  3.0e-12  1.09e+00   -3.473505027e+00  -3.473505111e+00  1.2e-09  0.03  
28  2.2e-08  6.3e-09  2.9e-12  1.15e+00   -3.473505032e+00  -3.473505113e+00  1.2e-09  0.03  
29  1.9e-08  5.9e-09  2.6e-12  9.96e-01   -3.473505040e+00  -3.473505116e+00  1.1e-09  0.03  
30  2.3e-08  5.9e-09  2.6e-12  8.83e-01   -3.473505040e+00  -3.473505116e+00  1.1e-09  0.03  
31  2.5e-08  5.8e-09  2.5e-12  1.00e+00   -3.473505043e+00  -3.473505117e+00  1.1e-09  0.03  
32  2.6e-08  5.7e-09  2.4e-12  9.33e-01   -3.473505044e+00  -3.473505117e+00  1.1e-09  0.03  
33  2.5e-08  5.7e-09  2.4e-12  1.02e+00   -3.473505044e+00  -3.473505117e+00  1.1e-09  0.03  
34  2.6e-08  5.7e-09  2.4e-12  1.40e+00   -3.473505045e+00  -3.473505118e+00  1.1e-09  0.03  
35  2.5e-08  5.6e-09  2.4e-12  8.99e-01   -3.473505045e+00  -3.473505118e+00  1.1e-09  0.03  
36  2.6e-08  5.6e-09  2.4e-12  1.06e+00   -3.473505045e+00  -3.473505118e+00  1.1e-09  0.04  
37  2.6e-08  5.4e-09  2.3e-12  9.98e-01   -3.473505049e+00  -3.473505119e+00  1.0e-09  0.04  
38  2.7e-08  5.4e-09  2.2e-12  1.00e+00   -3.473505050e+00  -3.473505119e+00  1.0e-09  0.04  
39  2.7e-08  5.4e-09  2.2e-12  9.96e-01   -3.473505050e+00  -3.473505119e+00  1.0e-09  0.04  
40  2.7e-08  5.4e-09  2.2e-12  9.98e-01   -3.473505050e+00  -3.473505119e+00  1.0e-09  0.04  
41  2.7e-08  5.4e-09  2.2e-12  9.98e-01   -3.473505050e+00  -3.473505119e+00  1.0e-09  0.04  
42  2.7e-08  5.4e-09  2.2e-12  9.98e-01   -3.473505050e+00  -3.473505119e+00  1.0e-09  0.04  
43  1.5e-09  1.7e-10  1.4e-14  9.87e-01   -3.473505154e+00  -3.473505156e+00  3.5e-11  0.04  
Optimizer terminated. Time: 0.05    


Interior-point solution summary
  Problem status  : PRIMAL_AND_DUAL_FEASIBLE
  Solution status : OPTIMAL
  Primal.  obj: -3.4735051535e+00   nrm: 9e+00    Viol.  con: 1e-09    var: 2e-11    cones: 0e+00  
  Dual.    obj: -3.4735051558e+00   nrm: 3e+00    Viol.  con: 0e+00    var: 2e-10    cones: 0e+00  
Optimizer summary
  Optimizer                 -                        time: 0.05    
    Interior-point          - iterations : 43        time: 0.04    
      Basis identification  -                        time: 0.00    
        Primal              - iterations : 0         time: 0.00    
        Dual                - iterations : 0         time: 0.00    
        Clean primal        - iterations : 0         time: 0.00    
        Clean dual          - iterations : 0         time: 0.00    
    Simplex                 -                        time: 0.00    
      Primal simplex        - iterations : 0         time: 0.00    
      Dual simplex          - iterations : 0         time: 0.00    
    Mixed integer           - relaxations: 0         time: 0.00    

------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): +32.2496
 
 
Note: there is an extra capacitance between the 4th and 5th inverter in the chain.

Optimal scale factors are: 

x =

    3.0462
    2.6553
    4.3323
   12.4396
    1.0000
    1.3184
    2.2358
    5.2220