Code covered by the BSD License

4.38462
4.4 | 79 ratings Rate this file 67 Downloads (last 30 days) File Size: 328 KB File ID: #5685 Version: 1.1

# Writing Fast MATLAB Code

### Pascal Getreuer (view profile)

11 Aug 2004 (Updated )

Speed up your project with this collection of techniques.

### Editor's Notes:

This file was selected as MATLAB Central Pick of the Week

File Information
Description

Learn how to use the Profiler tool, vectorized functions, and other tricks to writing efficient MATLAB code. This article includes how to convert any array into a column vector, bounding a value without if statements, and repeating/tiling a vector without repmat.

Contents:
* Introduction
* The Profiler
* Array Preallocation
* JIT Acceleration
* Vectorization
* Inlining Simple Functions
* Referencing Operations
* Solving Ax=b
* Numerical Integration
* Signal Processing
* Miscellaneous Tricks

Acknowledgements

This file inspired Local Peaks and Guidelines For Writing Clean And Fast Code In Matlab.

MATLAB release MATLAB 7.7 (R2008b)
24 Oct 2015 furusuna yume

### furusuna yume (view profile)

01 Jul 2015 Azalin L

### Azalin L (view profile)

Hey Sam Thanks for pointing that out.

20 Mar 2015 Stephen Cobeldick

### Stephen Cobeldick (view profile)

A tidy introduction to writing faster MATLAB code. The PDF covers the main points to consider, the general advice given is sound, and the example code should be able to assist new MATLAB users.

However there are several mistakes, one of which actually slows code down:

* Using |find| when simple logical indexing would be faster: only two out of the nine code examples that use |find(...)| is actually required (both are in "Vectorized Logic"). In all other code examples they could be replaced by logical indexing, which would be faster and simpler code:

http://blogs.mathworks.com/steve/2008/01/28/logical-indexing/

* |ind2sub| is shown with only one output, whereas actually the row and column indices are returned in separate outputs. Thus the subscript indexing example is incorrect.

* Misleading statements like "Using preallocation with a frequently resizing cell array is even more beneficial than with double arrays": MATLAB's own documentation does not make any such statement, and clearly recommends preallocating numeric arrays. Numeric arrays are stored in contiguous memory locations, so preallocation is critical for them: this is reflected in the fact that this is the _very first topic_ on MATLAB's own "Improving Performance" page:

http://www.mathworks.com/help/matlab/matlab_prog/techniques-for-improving-performance.html

The section on preallocation does not mention some other ways to preallocate arrays, in particular:

1. Looping in reverse.

2. Allocating one scalar element at a specific location.

Both of these can be faster than allocating an entire array before commencing calculations.

* Non-standard terminology makes it difficult for readers to transfer this knowledge to MATLAB's own documentation. For example "per-element" operations are actually named "element-wise" or "array" operations by MATLAB, and what are called "indices" in this document are called "linear indices" by MATLAB:

http://www.mathworks.com/help/matlab/matlab_prog/array-vs-matrix-operations.html

* It would be significantly improved by hyperlinks to the relevant documentation webpages, e.g. for array preallocation, element-wise operations, etc., and for every function used in the code examples.

* No mention of |bsxfun|, one of the most significant and useful functions for fast and efficient vectorized code:

http://www.mathworks.com/help/matlab/ref/bsxfun.html

Comment only
03 Jul 2014 Aneesh

### Aneesh (view profile)

This should be standard issue with every copy of MATLAB. Very useful!

08 Apr 2014 Emre Ozan Alkan

### Emre Ozan Alkan (view profile)

Awesome! Thank you!

02 Oct 2012 Manu

### Manu (view profile)

29 Jul 2012 Michael

### Michael (view profile)

30 Mar 2012 Olexander Zhytenko

### Olexander Zhytenko (view profile)

very good document

18 Feb 2012 Olexander Zhytenko

### Olexander Zhytenko (view profile)

Good, Thanks!

Comment only
24 Jan 2012 Sven Koerner

### Sven Koerner (view profile)

27 Jun 2011 David Smith

### David Smith (view profile)

28 Jan 2011 Michael Völker

### Michael Völker (view profile)

30 Dec 2010 Luis Andres

### Luis Andres (view profile)

Good work!

23 Sep 2010 Savas

### Savas (view profile)

Thanks a lot. THis will have a big effect on my code

28 Apr 2010 Javier Lopez-Calderon

### Javier Lopez-Calderon (view profile)

Great, Thanks!

03 Apr 2010 Nitin

### Nitin (view profile)

07 Aug 2009 Danila

### Danila (view profile)

19 May 2009 Leonardo Glavina

### Leonardo Glavina (view profile)

09 Jan 2009 Aniket

### Aniket (view profile)

very well written guide..thanks

31 Dec 2008 Nguyen Thang

Good, Thanks!

Comment only
29 Nov 2008 sara

### sara (view profile)

28 Nov 2008 Luigi Giaccari

### Luigi Giaccari (view profile)

Thanks sometimes pdf are better than m-file.

25 Nov 2008 Sunil

### Sunil (view profile)

thank u for such kind information. really helpful tips and please would you suggest me that i have a problem regarding execution time of for loop which i have to execute for 262144 times and its taking too much time about 2 mins so what should i do to reduce the execution time even i have used the preallocation of resultant matrix.

11 Oct 2008 Juan Pablo Arias
04 Oct 2008 Khanh Vo

I forgot rating. :)))

04 Oct 2008 Khanh Vo

Thanks a lot for this. A much for any people speaks MATLAB.

Comment only
28 Sep 2008 Gamal Alkirshi

08 Sep 2008 AMIT RAJ
02 Sep 2008 Husam Aldahiyat

This is so amazing and helpful. I've been struggling with slow executing functions and million element matrices for a long time but now it's all solved. Thanks a lot Mr. and know that you've been a lot of help. A LOT.

14 Aug 2008 Abel Brown

Indeed, a very good read ... should talk about things like bsxfun and how mex files compare to past and current matlab speeds. How about a section on I/O and string parsing.

07 Aug 2008 nick .

Nice little read with some random tips.

07 Aug 2008 ritesh shah
26 Jul 2008 abiodun olaluwe

kudos guy. I believe this meet sure meet the yearning fast majority of novice MATLAB users the world over.

16 Jul 2008 taneat zaetung
15 Jul 2008 Issac Niwas S
06 Jul 2008 marie billa

good

Comment only
19 Jun 2008 khaled darwish
08 May 2008 Elias Pipping
01 May 2008 chandra Guntupalli
01 May 2008 chandra Guntupalli
26 Mar 2008 biswa bhusan

nice

23 Mar 2008 Dan Cohn

Kudos, very informative and well written. Thank you for your good efforts!

15 Feb 2008 ntobeko zulu

none

01 Jan 2008 burhan rasito

wow its very exciting

01 Dec 2007 Hari Kumar

Well written article. Quite useful. Thanks.

24 Sep 2007 oktay gültekin

very usefull

thx

Comment only
22 Sep 2007 dawuni mohammed

i'm a student interested in this field.

06 Sep 2007 yiseth brango

excelente

Comment only
03 Aug 2007 Kyoung ho Chong

Very useful tip!! I love it

20 Jul 2007 Norbert P.
03 Jul 2007 Sam Clanton

I love it, Azalin.. way to face off against bad grammar with even worse...

Comment only
12 May 2007 emanuel luduvicce
06 Mar 2007 Robson Mariano
02 Mar 2007 Azalin L

there were some grammar errors...but I guess your a French speaker

apart from that...it was descent

01 Mar 2007 Christoph Ullrich

Very good short introduction to optimizing m-files!

23 Jan 2007 Simone Rabaovic
03 Jan 2007 Vishnuvenkatesh Dhage
21 Dec 2006 A M
14 Dec 2006 ali ahsan

fair try

15 Nov 2006 Sarah Miles

Excellent work.
You may want to correct the submission date. Thought it was old but realised when opened it that it was writen in June 2006.

Very good

12 Oct 2006 Orlando Rodríguez

Excellent stuff.

11 Oct 2006 Guillermo Ruiz

Thanks you are really good people

05 Apr 2006 asd asdf
26 Feb 2006 Ramin Moshfegh

Great Job

07 Feb 2006 deepak panwar
05 Feb 2006 Jq Yin
13 Dec 2005 Syed Husain

It's a great helping tool.

30 Nov 2005 Jas Ellis

10 Nov 2005 Gerald Corzo
14 Oct 2005 Nemo Managna

Yes it's a good idea to use the profiler. Using the profiler, I found that Pascal's recommended matrix initial code A = s(ones(m,n)) is four times slower than the simpler A(1:m,1:n) = s or A = s +zeros(m,n)

08 Oct 2005 sivasankaran sivanandam
07 Oct 2005 Ahmed Ayoub
19 Sep 2005 smita parija

itis moreuseful

12 Sep 2005 maomun munmao

fillfull

11 Jul 2005 Izru Garner

Useful

04 Jul 2005 ALoser IAm

10 May 2005 karthik lakshmanan
06 May 2005 O. L.

As a beginner, I have found everything clear, fast reading, and useful. Good job!

02 Apr 2005 Nabil nabil

very good document

24 Jan 2005 Troels Pedersen

Very good description of the indexing features of matlab. Please not that transposing a matrix using ' will complex conjungate the elements aswell. Therefore to create a row-vector by A(:)' should be done with care. Alternatively I think that transpose(A(:)) should be used.

05 Jan 2005 Rene Just Nielsen

A nice (and brief) collection of useful tips.

19 Aug 2004 James Alaly

Thanks, this is a great basic guide to speeding up Matlab code. I wish I had it a year ago when I started with Matlab.

As a note though, the method shown to avoid repmat is rarely faster (in Matlab 6.5) and usually slower than actually using repmat.

But thanks for the work you put into this, I printed it out and keep it next to Richard Johnson's "Matlab Programming Style Guidelines" on my ML shelf.

It's great

14 Aug 2004 Pascal Getreuer

***Response to review***

(1) ?numel? is not a function as of MATLAB 5.3 (what usually work with). It is a standard function by version 6.1.

(2) It is true that min and max operate over columns rather than entire matrices (the article includes some discussion on this). Thus the suggested methods involving min and max include matrix to vector conversion (using "A(:)" changes A to a vector). It works for matrices and n-D matrices of all sizes.

(3) The advantage of the not repmat method is that there is no function call -- it won't be significantly faster for a single tiling but can make a difference for many separate tiling operations. Furthermore, the standard m-files in MATLAB 4.0 and earlier don't include repmat, so this method is also more compatible.

(4) MEX is not a topic of discussion in this article, only mentioned. I agree it is much more difficult to write and peer and should only be a last resort.

(5) And yes, looping has a fair bit of overhead. Try the profiler on a for loop with many iterations and a one-line inner loop.

Comment only

You should look into NUMEL rather then prod(size(x)). Also be careful about recommending any or all or even min and max. they operate on vectors and NOT the entire matrix! You suggestions about not repmat are awful. I tried each one of your examples and found that was the same speed or faster. My matrices had around 5 million numbers in them. The last thing I would recommend is the use of MEX files. While it can be faster, it will take that much longer to write, peer, and debug. Did you check the speed of looping in matlab?

07 Sep 2005

Various fixes and revision

01 Dec 2005

24 Jan 2006