vectorizing or speeding looped code
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i am trying to speed up some code with multiple functions and have found the one that takes the most time (it is all a converted fortran code).  it runs a nested for loop 4 times (each with modified input). i've had some success elsewhere in the code eliminating slow points but this one just cant get right.  any ideas?  (in 2016b for compatability reasons)
for II= 1:N
    XP(1)= 1.0D0;
    for JJ=2:IORD1
        XP(JJ)=XP(JJ-1)*double(A1(II));
    end
    for JJ= 1:IORD1
        for KK= 1:IORD1
            B(JJ,KK)=B(JJ,KK)+XP(JJ)*XP(KK);
        end
        C(JJ)=C(JJ)+XP(JJ)*A2(II);
    end
end
0 Comments
Answers (3)
  Turlough Hughes
      
 on 22 Sep 2020
        This should help, though I've already made assumptions about the sizes of arrays. How many rows/columns are in each variable?
XP(1) = 1;
for II= 1:N
    XP(2:end) = XP(1:end-1)*double(A1(II));
    B = B + XP(:).*XP(:).';
    C = C + XP*A2(II);
end
2 Comments
  Turlough Hughes
      
 on 22 Sep 2020
				Did the code work? 
Some questions: is XP a column vector/row vector? Does A2 have as many elements as XP? Also, does B contain IORD1 rows and columns? Similarly does C have IORD1 elements?
  Paul Schenk
 on 22 Sep 2020
        2 Comments
  Turlough Hughes
      
 on 23 Sep 2020
				Vectorisation is usually faster but not always. Probably best to just provide a minimum working example (google it) of code that I (or others) can test and profile. Otherwise it really is just guess work. 
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