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basic scientific python, using python numeric, building simple extensions, mpi parallel programming in Python
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Python is a programming language designed with ease of programming and readable code as its foremost goals. Python has risen to prominence in scientific computing as the ideal tool for doing data conversions, scripting parameter studies, and in facilitating the scientific workflow. In this online course, a quick overview of the language is presented, along with a few tricks to maximize the utility of Python for engineering and science modeling.
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Introduction to ParaView software.
Slides for this presentation are available here:http://extremecomputingtraining.anl.gov/files/2016/08/Baur_1100aug10_IntroductionToParaView-ATPESC2016.pdf
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TACC
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Prerequisites: Linux, C/Fortran/Python, HPC Cluster Programming Environement This one day workshop will introduce participants to the four data intensive computing modes Stampede is designed to provide: 1) high throughput data processing, 2) parallel data analysis, 3) large shared memory applications, and 4) large-scale visualization. The material will focus on using the job launchers, parallel R, and visualization tools available on Stampede. The workshop will use a mixture of lecture and hands-on training to explore how users can use Stampede for their data driven computing needs. |
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While Python is a scripting language, it has plenty of facilities for high performance computing. This article covers some of its features and libraries that are particularly helpful when moving scientific code to a large cluster resource. It also includes specific recipes for compilation and execution on the TACC clusters.
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Discussion on I/O performance, Darshan tool for I/O characterization
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Introduction on python and its benefits in high performance computing and ease of use.
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Discussion of benefits of community development and codes for astrophysics
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