How to optimize code for GPU and remove for loops?

Hello, I am trying to optimize this code for GPU in order to speed up calculations. Here is small data sample, but mine data is quite big (1000000x100) and there can be a number of this size arrays. I was trying to use arrayfun but due to indexing it was not an option. 3D arrays were used as well with no luck to achieve my goal. The idea of code is to eliminate pair duplicates. Here is sample for, which due to for loops and other is very slow for big data:

      x1=[2 1 4 5 3;5 2 3 3 4;5 4 1 1 2;3 5 1 4 2;3 3 2 1 2];
  idx1=[1 1 0 0 1;1 1 1 0 0;1 1 0 1 1;1 0 1 1 1;1 1 1 1 1];
  idx=gpuArray(idx1);
  x=gpuArray(x1);
  [n1 n2]=size(x);
  for i=1:n1
  c(i,:)=x(i,x(i,:));
  end
  for j=1:n1  
          idx2(j)={find(idx(j,:)>0)};
              tempIdx=ones(size(idx(j,:)));
          idx3(j)={find(idx(j,:)>0)};
          for i=1:n2 
          if(i==c(j,i))
          if any(c(j,i)==idx2{j})
              if tempIdx(c(j,i)==idx2{j})==1
              idx2{j}(c(j,i)==idx2{j})=NaN;
              tempIdx(x(j,i))=0;  
              end
          end
          end
          end

end

Array x represents pairs and array idx represents the invoking of pair.

[Mantas Vaitonis]

Does anyone have any idea?

[umichguy84]

Can you explain in words what your trying to achieve. I'm not sure what you mean by pair duplicates.

[Mantas Vaitonis]

Hello, It is no longer necessary, did find a solution.