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Julia is a widely used high-level, general-purpose, interpreted programming language. It is often used as the "glue" within the High Performance Computing community.high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments |
Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. Julia’s Base library, largely written in Julia itself, also integrates mature, best-of-breed open source C and Fortran libraries for linear algebra, random number generation, signal processing, and string processing. In addition, the Julia developer community is contributing a number of external packages through Julia’s built-in package manager at a rapid pace. IJulia, a collaboration between the Jupyter and Julia communities, provides a powerful browser-based graphical notebook interface to Julia.
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- Connect to the Tufts High Performance Compute Cluster. See Connecting Access for a detailed guide.
Load the Julia module with the following command:
Code Block module load julia
Note that you can see a list of all available modules (potentially including different versions of Julia) by typing:
Code Block module avail
You can specify a specific version of Python with the module load command or use the generic module name (python) to load the latest version.
Start a Python Julia session by typing:
Code Block julia
Code Block printprintln("Hello,hello World!world")
For a more detailed overview of Julia and how it relates to Big Data or High Performance Computing (HPC) please contact tts-research@tufts.edu for information regarding future workshops.
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