  As modern scientific simulations grow ever more in size and complexity, even
their analysis and post-processing becomes increasingly demanding, calling for
the use of HPC resources and methods. yt is a parallel, open source
post-processing python package for numerical simulations in astrophysics, made
popular by its cross-format compatibility, its active community of developers
and its integration with several other professional Python instruments. The
Intel Distribution for Python enhances yt's performance and parallel
scalability, through the optimization of lower-level libraries Numpy and Scipy,
which make use of the optimized Intel Math Kernel Library (Intel-MKL) and the
Intel MPI library for distributed computing. The library package yt is used for
several analysis tasks, including integration of derived quantities, volumetric
rendering, 2D phase plots, cosmological halo analysis and production of
synthetic X-ray observation. In this paper, we provide a brief tutorial for the
installation of yt and the Intel Distribution for Python, and the execution of
each analysis task. Compared to the Anaconda python distribution, using the
provided solution one can achieve net speedups up to 4.6x on Intel Xeon
Scalable processors (codename Skylake).
