ARCHER, the UK's national supercomputing service, offers training in software development and high-performance computing to scientists and researchers throughout the UK. As part of our training service we will be running a 2 day 'Introduction of Scientific Programming with Python' training session.

Details

This course is aimed at programmers with little or no Python knowledge seeking to learn how to use Python for scientific computing. We will introduce Python's fundamental scientific libraries numpy, scipy and matplotlib. We will also introduce how to interface Python with Fortran and C codes, along with parallel programming methods including MPI via mpi4py.

This course is free to all academics.

Trainers

Kevin Stratford
Kevin has a background in computational physics and joined EPCC in 2001. He teaches on courses including 'Scientific Programming with Python' and 'GPU Programming with CUDA'.

Juan Rodriguez Herrera
Juan is involved in teaching ARCHER courses related to HPC, MPI, and Python, among others. He's a certified instructor of Software and Data Carpentry workshops. He also supervises EPCC's MSc dissertation projects.

Structure

The course will be delivered over two days in person. The course will interleave many practical exercises with short lectures and discussions.

Pre-requisites

To attend, you must have some experience of writing code and/or scripts and be familiar with programming concepts including conditionals, loops, arrays and functions. You should also have some basic knowledge of the Python language. For an introduction to Python, please see Code Academy's Python tutorial: https://www.codecademy.com/tracks/python

You should also be comfortable with using the bash shell. For an introduction to the shell, please see, for example Software Carpentry's lessons on Unix Shell: https://swcarpentry.github.io/shell-novice/

The course will be hands-on, and you should bring your own laptop.

We recommend you download, before the course, Anaconda python Version 3.6 from https://www.anaconda.com/download/ (version 2.7 will work at a stretch). This has the packages required (and more).

Please download the course material (link below).

Timetable

Day 1

09:45 - Registration and check installations
10:15 - L01 : Introduction
11:15 - Break
11:30 - L02 : NumPy
13:00 - Lunch
14:00 - L03 : Matplotlib
15:30 - Break
16:00 - Exercises
17:00 - end
Day 2

10:00 - L04 : SciPy
11:00 - Break
11:30 - L05 : Fortran/C Interfaces
13:00 - Lunch
14:00 - L06 : Python classes
15:30 - Break
15:45 - L07 : Parallel processing and mpi4py; ARCHER Exercise
16:45 - end
Course Materials

Slides and exercise material for this course.

https://events.prace-ri.eu/event/758/