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Re: CPU time, Octave vs MATLAB

From: Ian McCallion
Subject: Re: CPU time, Octave vs MATLAB
Date: Tue, 10 Mar 2020 14:50:11 +0000

On Tue, 10 Mar 2020 at 14:31, Rory Conolly <address@hidden> wrote:
> On Tue, Mar 10, 2020 at 10:08 AM Kai Torben Ohlhus <address@hidden> wrote:
>> On 3/10/20 9:39 PM, Rory Conolly wrote:
>> > I have a program that describes biological mechanisms of cancer. Running
>> > the code in MATLAB takes 112 minutes. The almost identical code in
>> > Octave takes about 10 hr, so about 5 times slower. Is this an expected
>> > difference between Octave and MATLAB or more likely due to something in
>> > my code? Code is hundreds of lines over several files.
>> >
>> > - Rory
>> >
>> Dear Rory,
>> Unless you present (a meaningful portion of) your code, it is fortune
>> telling and blind guessing what could be wrong.  Most likely your code
>> is not properly vectorized [1] and uses lots of nested loops, e.g.
>> for k = 1:P
>>   for i = 1:M
>>     for j = 1:N
>>       A(i,j) = A(i,j) + B(i,j);
>>     endfor
>>   endfor
>> endfor
>> You can make use of profiling [2] to find the bottlenecks.
>> HTH,
>> Kai
>> [1]
>> [2]
> Kai, thanks for your input. My question is more about the relative speed of 
> Octave vs MATLAB. My code was originally developed in MATLAB and is 
> vectorized. The code reads parameter values from an Excel file. The Octave 
> call to Excel requires the file extension while the MATLAB call does not. So 
> that’s the only modification of the code running in Octave. So the two codes 
> are pretty much identical, but the Octave code runs much more slowly. Happy 
> to provide the code but it’s in several files and probably a thousand or more 
> lines.

Octave generally is nothing like 5 times slower than Matlab. My own
code for example runs at about the same speed. However I believe
Matlab has worked hard to improve nested loop performance in
particular. Hence Kai's suggestions.

Vectorisation also improves quality and readability. Go for it!

Cheers... Ian

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