How to reduce computation time for this loop. My more than 90% of time is consume by this subsection

for h=1:r
  dist(h, :) = sum(bsxfun(@minus, data(h,:), mtrx).^2, 2)';
end

I have tried parfor loop also, but this does not solve my problem. Instead of decreasing computation time. It increases computation time. Please help me to solve this problem.

Answer 1

[Sean de Wolski]

Is dist preallocated?

How much does it speed up if you run it backwards to dynamically preallocate?

for h = r:-1:1
  dist(h, :) = sum(bsxfun(@minus, data(h,:), mtrx).^2, 2)';
end

[kusum bharti]

Yes i have prallocated dist. but still it is slow. What to do

[kusum bharti]

Is there any way to reduce computation time

[José-Luis]

How big are r, data, and mtrx?

Answer 2

[Matt J]

This works column-wise instead of row-wise and gives Euclidean distance instead of square distance, but is otherwise the same as what you've asked for,

function Graph=interdists(A,B)
%Finds the graph of distances between point coordinates
%
% (1) Graph=interdists(A,B)
%
% in:
% 
% A:  matrix whose columns are coordinates of points, for example 
%          [[x1;y1;z1], [x2;y2;z2] ,..., [xM;yM;zM]]
%     but the columns may be points in a space of any dimension, not just 3D.
% 
% B:  A second matrix whose columns are coordinates of points in the same
%     Euclidean space. Default B=A.
% 
% 
% out:
% 
% Graph: The MxN  matrix of separation distances in l2 norm between the coordinates. 
%        Namely, Graph(i,j) will be the distance between A(:,i) and B(:,j).
%
%
% (2) interdists(A,'noself') is the same as interdists(A), except the output 
%     diagonals will be NaN instead of zero. Hence, for example, operations
%     like min(interdists(A,'noself')) will ignore self-distances.
%
% See also getgraph

noself=false;
if nargin<2  
    B=A; 
elseif ischar(B)&&strcmpi(B,'noself')
    noself=true;
    B=A;
end

[N,M]=size(A);
B=reshape(B,N,1,[]);

Graph=sqrt(sum(bsxfun(@minus, A, B).^2,1));

Graph=reshape(Graph,M,[]);

if noself
    n=length(Graph);
   Graph(linspace(1,n^2,n))=nan; 
end