MATLAB1 - Revision history

GethinWilliams: /* Finding where your code is slow */

2014-03-07T12:08:30Z

Finding where your code is slow

2013-09-23T10:38:38Z

2013-09-06T09:24:56Z

Preallocation of Vectors

2013-09-06T09:23:51Z

Hints and Tips on Performance

2013-09-03T15:40:27Z

Introduction

2013-09-03T15:30:40Z

Preallocation of Vectors

2013-09-03T15:23:28Z

2013-09-03T15:22:29Z

Built-in Functions

2013-09-03T14:58:30Z

Finding where your code is slow

2013-09-03T14:55:30Z

Finding where your code is slow

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    cart2plr(rand(),rand());
 end
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 * '''any''' and '''all''': will return true if any or all of the elements of a vector or matrix are true (>0), respectively.
 * '''find''':  returns the indices of a vector that satisfy the given expression.  For example, '''find(vec > 7)''' returns the indices of all elements of vec that are greater than 7.
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-However, this flexibility will come at the cost of performance, as the frequent resizing of the container ''vec'' will incur many requests for additional memory for storage.  Therefore, it is wise to pre-allocate storage, if you can predict ahead of time how large the container needs to be.
+However, this flexibility will come at the cost of performance, as the frequent resizing of the container ''vec'' will incur many requests for additional memory for storage.  Therefore, it is wise to pre-allocate storage, if you can predict ahead of time how large the container needs to be.  This is probably the simplest way in which you can speed up your MATLAB code.
 To demonstrate the benefit of pre-allocation, consider the following two MATLAB scripts.

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 There are several aspects of some MATLAB code that can really limit it's performance.  For loops are a common limiting factor, as is allocation of memory on-the-fly.  These limitations can often be addressed by:
 * Replacing loops over the elements of a vector or matrix with:
 ** Scalar and array operations.
 ** Built-in functions which take vectors or matrices as arguments.
 However, before we get into examples of improved code, we need to determine '''where''' your code is spending the majority of it's time.  It would not be sensible to invest lots of effort in re-writing a section of your program which took only 1% of the overall runtime.  Accordingly, the next section focusses on methods for finding ''hot spots'' in your code:
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 [[Image:MATLAB-Profiler.png|thumb|800px|none|The MATLAB profiler]]
 ==Preallocation of Vectors==
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 Elapsed time is 0.279115 seconds.
 </pre>
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 Rather than re-invent the wheel, we'll use some tried and tested tutorial material.  The following notes from the Maths department at the University of Dundee are concise, comprehensive, but also easy to read:
 http://www.maths.dundee.ac.uk/ftp/na-reports/MatlabNotes.pdf
 =Hints and Tips on Performance=

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 ==Preallocation of Vectors==
-Consider the following two MATLAB scripts.
+Memory allocation is an expensive operation.  MATLAB will allow us to assign values to an array inside a loop, where the array keeps growing to accommodate all the iterations of the loop.  For example:
 '''noprealloc.m''':
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 tic;
 for i=1:3000,
-for j=1:3000,
+  for j=1:3000,
-x(i,j)=i+j;
+    x(i,j)=i+j;
-end
+  end
 end
 toc
@@ Line 126: / Line 136: @@
 x=zeros(3000);
 for i=1:3000,
-for j=1:3000,
+  for j=1:3000,
-x(i,j)=i+j;
+    x(i,j)=i+j;
-end
+  end
 end
 toc
 </source>
-When we run these two scripts (on BCp2), we see a marked difference in the runtime:
+When we run these two scripts (on BCp2), we see a ''significant'' difference in the runtime:
 <pre>

← Older revision		Revision as of 15:22, 3 September 2013
Line 97:		Line 97:

	==Built-in Functions==		==Built-in Functions==
		+
		+	MATLAB contains a number of built-in functions which can save you from writing a loop. Examples include:
		+
		+	* '''sum''' and '''prod''': which compute the sum or product, respectively, of all the elements of vector.
		+	* '''cumsum''' and '''cumprod''': both return a vector and are the cumulative counterparts of ''''sum''' and '''prod'''.
		+	* '''min''' and '''max'''.
		+	* '''any''' and '''all''': will return true if any or all of the elements of a vector or matrix are true (>0), respectively.
		+	* '''find''': returns the indices of a vector that satisfy the given expression. For example, '''find(vec > 7)''' returns the indices of all elements of vec that are greater than 7.

	==Preallocation of Vectors==		==Preallocation of Vectors==

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 ==Scalar and Array Operators==

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 </pre>
-A more detailed analysis can be elicited from the MATLAB profiler.  For example
+A more detailed analysis can be elicited from the MATLAB profiler.  Let's suppose we have a function which converts cartesian to polar coordinates:
 <source lang="matlab">
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-plot(magic(35))
+for i=1:3000
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