Tutorial slides (PDF) - Clemson University

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Resources Python http://www.python.org/ all the current documentation, software, tutorials, news, and pointers to advice you'll ever need GPAW https://wiki.fysik.dtu.dk/gpaw/ GPAW documentation and code SciPy and NumPy http://numpy.scipy.org/ The official NumPy website http://conference.scipy.org/ The annual SciPy conference http://www.enthought.com/ Enthought, Inc. the commercial sponsors of SciPy, NumPy, Chaco, EPD and more Matplotlib http://matplotlib.sourceforge.net/ best 2D package on the planet mpi4py http://mpi4py.scipy.org/
Yet More Resources Tau http://www.cs.uoregon.edu/research/tau/home.php official open source site http://www.paratools.com/index.php commercial tools and support for Tau web2py http://www.web2py.com/ web framework used in this tutorial
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Python for Scientific and High Perf
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Overview We seek to cover: Python l
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1. Introduction Introductions Tutor
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Why Use Python for Scientific Compu
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Please login to the Tutorial Enviro
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Interpreters CPython Standard pytho
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CPython Interpreter Notes Compilati
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Built-in Numeric Types int, float,
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Gotchas with Built-in Numeric Types
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Built-in Sequence Types str, unicod
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Built-in Sequence & Mapping Type Go
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Control Structures for - iterative
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List Comprehensions List Comprehens
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File I/O Basics Most I/O in Python
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Let's write ten integers to disk wi
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Modules import - load module, defin
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N-dimensional homogeneous arrays (n
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Slicing Arrays >>> a = np.array([[1
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SciPy Extends NumPy with common sci
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Python Threading Python threads rea
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Implementation Example: Calculating
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Subprocess The subprocess module al
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Calculating pi with multiprocessing
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mpi4py wraps your native mpi prefer
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from mpi4py import MPI import numpy
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Python Best Practices for Performan
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Outline a massively parallel Python
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GPAW Strong-scaling Results
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KS-DFT is a complex algorithm!
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Performance Mantra People are able
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NumPy - Memory How big is your bina
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NumPy - FLOPS WARNING: If you make
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Profiling Mixed Python-C code Numbe
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Parallel Python Interpreter and Deb
Page 69 and 70: Profiling Mixed Python-C code Flat
Page 71 and 72: Python Interface to BLACS and ScaLA
Page 79 and 80: Python Interface in BLACS and ScaLA
Page 81 and 82: Python Interface in BLACS and ScaLA
Page 83 and 84: The Bad & Ugly: NumPy cross-compile
Page 85 and 86: Python for plotting and visualizati
Page 87 and 88: From Lib to App (overview) Numerica
Page 89 and 90: From Lib to App (overview) Storage
Page 91 and 92: Ruby on Rails Django TurboGears Pyl
Page 93 and 94: matplotlib gallery
Page 95 and 96: application1 application 2 applicat
Page 97 and 98: application 1 application=” dna
Page 99 and 100: web2py and Dispatching hostnam e
Page 101 and 102: web2py and Dispatching controller
Page 103 and 104: Upload DNA Seq. {{=form}} web2py a
Page 105 and 106: web2py and Authentication authentic
Page 107 and 108: web2py web based IDE web based IDE
Page 109 and 110: Before we start download web2py fro
Page 111 and 112: Define some algorithms def find_gen
Page 113 and 114: Define actions in controllers/defau
Page 115 and 116: Try it
Page 117 and 118: Define Actions in controllers/defau
Page 119: Try it
Page 123 and 124: Let's review!
Page 125: This work is supported in part by t
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Tutorial slides (PDF) - Clemson University

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