This is a WEBCAST training event by Texas Advanced Computing Center (TACC)

As HPC widens its vision to include big data and non-traditional applications, it must also embrace languages that are easier for the novice, more robust for general computing, and more productive for the expert. One candidate language is Python. Python is a versatile language with tools as diverse as visualizing large amounts of data, creating innovative user interfaces, and running large distributed jobs. Unfortunately, Python has a reputation for poor performance. In this tutorial, we give a user practical experience using Python for scientific computing tasks. Topics include array computing with NumPy, interactive development with IPython, low-level C linking with Cython, distributed computing with MPI, and performance issues.

Recommended prerequisites:

Basic programming knowledge with Python. A good tutorial is available online here:

http://docs.python.org/tutorial/

Remote attendees can install the used libraries versions (all included in Anaconda Pro or Enthought Python Distribution (which doesn’t include mpi4py):

Python 2.7
numpy 1.6
scipy 0.10
IPython 0.12
cython 0.15
mpi4py 1.2.2

Staff support for remote users will be limited; however, the lecturers will field questions.

Please register with TACC (http://www.tacc.utexas.edu/user-services/training/python-for-hpc) or XSEDE (https://www.xsede.org/web/xup/course-calendar/-/training/class/67)

HPC@LSU will broadcast this training and user services consultants will be available to answer any questions. If you plan on attending this broadcast, click the register button below. Seating is limited, so please register early.