{"id":175,"date":"2017-04-19T15:39:55","date_gmt":"2017-04-19T19:39:55","guid":{"rendered":"https:\/\/carleton.ca\/rcs\/?page_id=175"},"modified":"2021-07-29T10:25:09","modified_gmt":"2021-07-29T14:25:09","slug":"matlab-tips","status":"publish","type":"page","link":"https:\/\/carleton.ca\/rcs\/rcdc\/matlab-tips\/","title":{"rendered":"Matlab on Linux Servers"},"content":{"rendered":"

Using Parallelism in Matlab<\/h2>\n

One way to improve MATLAB code performance is using parallelism.\u00a0 In MATLAB, the most common way to do this is to replace a slow\u00a0for\u00a0<\/strong>loop with a\u00a0parfor<\/strong> loop.<\/p>\n

However, there are some restrictions on what loops can be converted to\u00a0parfor.\u00a0 Loops must be independent.\u00a0 That is, the loop iterations should be executable in any order, where the results of one iteration do not rely on previous iterations.<\/p>\n

More information on converting loops to parfor can be found at:\u00a0\u00a0https:\/\/www.mathworks.com\/help\/distcomp\/troubleshoot-variables-in-parfor-loops.html<\/a><\/p>\n

Using the Console<\/h2>\n

It is possible to use MATLAB without its graphical interface.\u00a0 In particular, on remote Linux servers it is often best to run MATLAB from the command-line and not interactively.<\/p>\n

Once your MATLAB code is finished and tested, you can run it from the Linux server’s shell:<\/p>\n

    \n
  1. SSH to remote server<\/li>\n
  2. Change directory to your MATLAB script’s location\u00a0(let’s assume your script is called myexample.m)<\/em><\/li>\n
  3. Run this command: matlab -nodisplay -r 'myexample; quit'<\/code><\/li>\n<\/ol>\n

    You can even put this MATLAB command in the background using techniques found at either:<\/p>\n