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.

For more information about Julia, you can visit the following resources:

httpshttp://www.pythonjulialang.org/

https://en.wikipedia.org/wiki/Python_(programming_language)

Getting Started with

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Julia

You can access and start using Python Jula with the following steps:

1. Connect to the Tufts High Performance Compute Cluster. See Connecting Access for a detailed guide.
   
   

2. Load the Python Julia module with the following command:

   Code Block
   module load pythonjulia

   Note that you can see a list of all available modules (potentially including different versions of PythonJulia) 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.

3. Start a Python Julia session by typing:

   Code Block
   pythonjulia

   Code Block
   printprintln("Hello,hello World!world")

Python related:

How can I verify if a particular Python package is installed?
Add-on tools such as numpy and scipy are installed. Others would be under the install tree located at:
/opt/shared/python/
in the version specific site-packages directory.   Another approach uses pip.

For a more detailed overview of Python Julia and how it relates to Big Data or High Performance Computing (HPC) please contact tts-research@tufts.edu for information regarding future workshops.