Dedicated distributed system to handle matlab jobs

I'm a software engineer and currently looking forward to setup a distributed system at my laboratory so that I can process some matlab jobs over them. I have looked into MATLAB MPI but I w开发者_如何学Goant to know if there is some way so that I can setup a system here without any FEE or AMOUNT.

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I have spent a lot of time looking at that very issue, and the short answer is: nope, not possible.

There are two long answers. First, if you're constrained to using Matlab, then all roads lead back to MathWorks. One possibility is that you could compile your code, you'd need to buy the compiler from Mathworks, though, and then you could run the compiled code on whatever grid infrastructure you wish, such as Hadoop.

Second, for this reason, I have found it much better to simply port code to another language, usually one in open source. For the work I tend to do, Octave is a poor replacement for Matlab. Instead, R and Python are great for most of the same functionality. Personally, I lean a lot more toward R than Python, but that's because R is a better fit for these applications (i.e. they're very statistical in nature).

I've ported a lot of Matlab code to R and it's not too bad. Porting to Python would be easier in general, though, and there is a very large Matlab refugee community that has switched to Python.

Once you're in either Python or R, there are a lot of options for MPI, multicore tools, distributed systems, GPU tools, and more. In fact, you may find the migration easier by writing some of the distributed functions in Python or R, loading up an easy to use grid system, and then have Matlab submit the job to the server. Your local code could be the same, but then you can work on porting only the gridded parts, which you'd probably have to devote some time to write in Matlab, anyway.

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I wouldn't say it's completely impossible; You can use TCP/IP sockets to build a client/server application (you will find many MEX implementations for BSD sockets on File Exchange).

The architecture is simple: your main MATLAB client script sends jobs (code along with any needed data serialized) to nodes to evaluate and send back results when done. These nodes would be distributed MATLAB instances running the server part which listens for connections, and runs anything it receive through the EVAL function.

Obviously it is up to write code that can be divided into breakable tasks.

This is not as sophisticated as what is offered by the Distributed Computing Toolbox, but basically does the same thing...