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.
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:
Getting Started with Julia
You can access and start using Jula with the following steps:
- Connect to the Tufts High Performance Compute Cluster. See Connecting for a detailed guide.
Load the Julia module with the following command:
module load julia
Note that you can see a list of all available modules (potentially including different versions of Julia) by typing:
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 session by typing:
julia
print("Hello, 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.