matlab提速技巧，自matlab帮助文件

matlab提速技巧（自matlab帮助文件）

1.首先要学会用profiler.

1.1. 打开profiler.

To open the Profiler, select View -> Profiler from the MATLAB desktop, or type profile viewer in the Command Window. The MATLAB Profiler opens.

在我的机器上是： 在matlab desktop下，Desktop->Profiler.

在M文件编辑器下，Tools->Open Profiler.

1.2. 运行profiler

可以把要运行的code拷入Run this code后面的输入框里。

You can run this example

[t,y] = ode23(\'lotka\',[0 2],[20;20])

也可以输入要运行的M文件名。

1.3.Click Start Profiling (or press Enter after entering the statement).

1.4. 查看Profile Detail Report

会告知你哪些代码消耗了多少时间，可以找到哪些函数或那些代码行消耗了主要的时间，或者是经常被调用。

也可以用stopwatch Timer函数，计算程序消耗时间

Use tic and toc as shown here.

tic

- run the program section to be timed -

toc

2. 加速1：向量化

MATLAB is a matrix language, which means it is designed for vector and matrix operations. You can often speed up your M-file code by using vectorizing algorithms that take advantage of this design. Vectorization means converting for and while loops to equivalent vector or matrix operations.

i = 0;

for t = 0:.01:1000

i = i+1;

y(i) = sin(t);

end

运行时间为30.776秒。

改为向量化代码：

t = 0:.01:1000;

y = sin(t);

运行时间为0秒。

Functions Used in Vectorizing

Some of the most commonly used functions for vectorizing are：

all

diff

ipermute

permute

reshape

squeeze

any

find

logical

prod

shiftdim

sub2ind

cumsum

ind2sub

ndgrid

repmat

sort

sum

3. 加速2：Preallocating Arrays（预分配空间）

You can often improve code execution time by preallocating the arrays that store output results. Preallocation makes it unnecessary for MATLAB to resize an array each time you enlarge it. Use the appropriate preallocation function for the kind of array you are working with.

Preallocation also helps reduce memory fragmentation if you work with large matrices.

4.加速其他方法：

Coding Loops in a MEX-File for Speed

If there are instances where you must use a for loop, consider coding the loop in a MEX-file. In this way, the loop executes much more quickly since the instructions in the loop do not have to be interpreted each time they execute.

Functions Are Faster Than Scripts

Your code will execute more quickly if it is implemented in a function rather than a script. Every time a script is used in MATLAB, it is loaded into memory and uated one line at a time. Functions, on the other hand, are compiled into pseudo-code and loaded into memory once. Therefore, additional calls to the function are faster.

Load and Save Are Faster Than File I/O Functions

If you have a choice of whether to use load and save instead of the MATLAB file I/O routines, choose the former. The load and save functions are optimized to run faster and reduce memory fragmentation.

Avoid Large Background Processes

Avoid running large processes in the background at the same time you are executing your program in MATLAB. This frees more CPU time for your MATLAB session.

5. 多线程

在matlab desktop里，File->Preferences->General->Multithreading, 看是否选择了Enable Multithreaded Computation。

如果没选，check it， 看是否有提速。