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Matlab-like tools for high-performance computing
Numbers Game
A common question from people who build both large and small HPC clusters is, "What applications can I run on my HPC system?"
One of the most popular applications is Matlab [1], which many people use in their everyday work and research – either Matlab or Matlab-like tools. For example, a fairly recent blog posting from Harvard University's Faculty of Arts and Sciences, Research Computing Group [2] showed that the second most popular Environment Module [3] was Matlab.
People are using Matlab for a variety of tasks that range from the humanities, to science, to engineering, to games, and more. Some researchers use it for parameter sweeps by launching 25,000 or more individual Matlab runs at the same time. Needless to say, Matlab is used very heavily at a number of places, so it is a very good candidate for running on an HPC system.
I don't want to take anything away from MathWorks, the creator of Matlab, because their product is a wonderful application, but for a number of reasons, Matlab might not be the answer for some people (e.g., they can't afford Matlab or can't afford 25,000 licenses, they just want to try a few Matlab features, or they want or need access to the source code). This brings up the category of tools typically called "Matlab-like"; that is, they try to emulate the concept of Matlab with compatible syntax so that moving back and forth is relatively easy. When people ask what tools or applications they can try on their shiny new cluster, I tend to recommend one of these Matlab-like tools, even though they aren't strictly parallel right out of the box (so to speak).
A few tools that are somewhat Matlab-like – some still surviving and some defunct – include RLaB, RLaB+, JMathlab, and O-Matrix (commercial). A whole host of other tools
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