MATLAB APPLICATION DEPLOYMENT - WEB EXAMPLE GUIDE Manuale Utente Scaricare il pdf (Pagina 9)

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Distributing Your MATLAB Code

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Example: Deploying a Compiled MATLAB Application

Two Approaches: Direct and Compiled

You can invoke a MATLAB executable from a GenePattern module using one of two approaches: the direct approach

or the compiled approach. Following are brief descriptions of each approach, including its advantages and

disadvantages:

● Direct approach. In the direct approach, the GenePattern task directly invokes the MATLAB executable, which

executes your M-code. This approach is best suited for use on a standalone GenePattern server, where you

already have a MATLAB license and you will not redistribute the MATLAB-based GenePattern modules to other

users who do not have their own MATLAB licenses. The advantages to this approach are: it is the simplest way

to getting your M-code running on GenePattern, it can be used for any MATLAB and GenePattern supported

platform, and it allows for easier modification of the M-code files as you modify your analysis. The disadvantages

of this approach are: it requires a MATLAB license for each concurrent user on the GenePattern server machine

and, if you change platforms, you must change the command line because different platforms have different

methods of passing arguments to MATLAB.

● Compiled approach. In the compiled approach, you use the MATLAB Compiler to generate a standalone

executable; the GenePattern task then invokes that executable. The advantages to this approach are: it allows

redistribution of the module to other GenePattern users who do not have their own MATLAB license and it can

be run on a shared server without needing to get a MATLAB license for each concurrent user. The

disadvantages are: it requires you to have a MATLAB Compiler license, it can be used only on platforms

supported by the MATLAB Compiler, it must be compiled separately for each platform, and the GenePattern

server must have the MATLAB Component Runtime (MCR) installed before it can run the compiler-generated

executable.

If you are simply using your M-code on your standalone GenePattern server, the direct approach is simpler; however,

if you want to give copies of your M-code to other people or deploy your M-code on a shared GenePattern server, the

compiled approach is preferred. The compiled approach may provide slightly better performance for fast running

tasks since the startup delay will be shorter, but the actual execution time will be approximately the same for either

approach.

MATLAB Versions

The instructions in this section are based on the following MATLAB versions:

● MATLAB 7.1 (part of Release 14). Earlier versions of MATLAB use a different (deprecated) mechanism for

deployment, which is not compatible with the instructions provided in this guide. For Mac OS X, these

instructions were tested using MATLAB 7.2.

● MATLAB Compiler 4.0 or later. The MATLAB Compiler is currently available on Windows, Unix, and Mac OS X;

therefore, these are the only platforms on which you may deploy a compiled MATLAB-based task. For Mac OS

X, these instructions were tested using the MATLAB Compiler 4.4.

The MATLAB Compiler generates executables only for the platform on which it is executing. For example, if you

create a MATLAB executable on Windows, the MATLAB-based module that invokes that executable can only be

deployed on a GenePattern server running under Windows. Therefore, you need a MATLAB (and MATLAB

Compiler) license for each platform on which you wish to deploy your executable.

Adapting Your MATLAB Code

When you create a task in GenePattern, you specify the command line that invokes the program that performs the

desired function. Generally, the command line includes arguments, such as the parameters for the algorithm and the

data file to analyze.

Calling script M-code from a command line is possible, but generally not useful because you cannot pass arguments

to the script. To pass arguments to your M-code, create a no-return entry function to serve as the top level call into

MATLAB. The following example defines a no-return entry function that accepts two parameters:

function analyzeThis ( filename, whatToWrite )

... (your M-code here)

Writing Modules for GenePattern provides additional guidelines for writing code that will run as a GenePattern task.

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MATLAB APPLICATION DEPLOYMENT - WEB EXAMPLE GUIDE Manuale Utente Pagina 9

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