It would be much more efficient to lump all of the multiplications together. Also, when you use for loops with codistributed arrays you need to use the drange command to make sure that the workers only operate on the data that they own. I think rewriting your code a bit will speed things up:
spmd
% Create the data. Don't use floor because that will return all zeros.
r = rand(100,codistributor1d(1));
end
% Find the norm of each row
norm_r = sqrt(sum(abs(r).^2,2));
% get the dimensions
[n_row n_col] = size(data);
% Scale each row by its norm first.
% Use drange so that each worker operates only on the data it owns/
spmd
for i=drange(1:n_row)
r(i,:) = r(i,:)/norm_r(i);
end
end
% Transpose the data so we can use matrix multiplication to
% perform the dot products all at once. A transpose is cheap and
% incurs no communication. Of course this is only useful if you have
% enough memory to store another copy of the local part on each worker.
tr = transpose(r);
res = r*tr;
