CODEWITHSUNDEEP
performancematlabmatrixheavy-computation
gmeroni
gmeroni

Reputation: 571

Speed up an Enumeration process

After a few days of optimization this is my code for an enumeration process that consist in finding the best combination for every row of W. The algorithm separates the matrix W in one where the elements of W are grather of LimiteInferiore (called W_legali) and one that have only element below the limit (called W_nlegali).

Using some parameters like Media (aka Mean), rho_b_legali The algorithm minimizes the total cost function. In the last part, I find where is the combination with the lowest value of objective function and save it in W_ottimo

As you can see the algorithm is not so "clean" and with very large matrix (142506x3000) is damn slow...So, can somebody help me to speed it up a little bit?

   for i=1:3000
   W = PesoIncertezza * MatriceCombinazioni';
   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

   W_legali = W;
   W_legali(W<LimiteInferiore) = nan;

   if i==1
        Media = W_legali;
        rho_b_legale = ones(size (W_legali,1),size(MatriceCombinazioni,1));
   else
        Media = (repmat(sum(W_tot_migl,2),1,size(MatriceCombinazioni,1))+W_legali)/(size(W_tot_migl,2)+1);
        rho_b_legale = repmat(((n_b+1)/i),1,size(MatriceCombinazioni,1));
   end

   [W_legali_migl,comb] = min(C_u .* Media .* (1./rho_b_legale) + (1./rho_b_legale) .* c_0 + (c_1./(i * rho_b_legale)),[],2);

   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

   MatriceCombinazioni_2 = MatriceCombinazioni;
   MatriceCombinazioni_2(sum(MatriceCombinazioni_2,2)<2,:)=[];

   W_nlegali = PesoIncertezza * MatriceCombinazioni_2';
   W_nlegali(W_nlegali>=LimiteInferiore) = nan;

   if i==1
        Media = W_nlegali;
        rho_b_nlegale = zeros(size (W_nlegali,1),size(MatriceCombinazioni_2,1));
   else
        Media = (repmat(sum(W_tot_migl,2),1,size(MatriceCombinazioni_2,1))+W_nlegali)/(size(W_tot_migl,2)+1);
        rho_b_nlegale = repmat(((n_b)/i),1,size(MatriceCombinazioni_2,1));
   end

   [W_nlegali_migliori,comb2] = min(C_u .* Media .* (1./rho_b_nlegale) + (1./rho_b_nlegale) .* c_0 + (c_1./(i * rho_b_nlegale)),[],2);

   z = [W_legali_migl, W_nlegali_migliori];

   [z_ott,comb3] = min(z,[],2);

   %Increasing n_b
   if i==1
       n_b = zeros(size(W,1),1);
   end

   index = find(comb3==1);
   increment = ones(size(index,1),1);
   B = accumarray(index,increment);
   nzIndex = (B ~= 0);
   n_b(nzIndex) = n_b(nzIndex) + B(nzIndex);

   %Using comb3 to find where is the best configuration, is in
   %W_legali or in W_nLegali?

   combinazione = comb.*logical(comb3==1) + comb2.*logical(comb3==2);
   W_ottimo = W(sub2ind(size(W),[1:size(W,1)],combinazione'))';

   W_tot_migl(:,i) = W_ottimo;
   FunzObb(:,i) = z_ott;


   [PesoCestelli] = Simulazione_GenerazioneNumeriCasuali (PianoSperimentale,NumeroCestelli,NumeroEsperimenti,Alfa);
   [PesoIncertezza_2] = Simulazione_GenerazioneIncertezza (NumeroCestelli,NumeroEsperimenti,IncertezzaCella,PesoCestelli);

   PesoIncertezza(MatriceCombinazioni(combinazione,:)~=0) = PesoIncertezza_2(MatriceCombinazioni(combinazione,:)~=0); %updating just the hoppers that has been discharged

end

Upvotes: 0

Views: 137

Answers (1)

chappjc
chappjc

Reputation: 30579

When you see repmat you should think bsxfun. For example, replace:

Media = (repmat(sum(W_tot_migl,2),1,size(MatriceCombinazioni,1))+W_legali) / ...
    (size(W_tot_migl,2)+1);

with

Media = bsxfun(@plus,sum(W_tot_migl,2),W_legali) / ...
    (size(W_tot_migl,2)+1);

The purpose of bsxfun is to do a virtual "singleton expansion" like repmat, without actually replicating the array into a matrix of the same size as W_legali.

Also note that in the above code, sum(W_tot_migl,2) is computed twice. There are other small optimizations, but changing to bsxfun should give you a good improvement.

The values of 1./rho_b_legale are effectively computed three times. Store this quotient matrix.

Upvotes: 1

Related Questions