- Page 1 and 2: Python for Scientific and High Perf
- Page 3 and 4: Overview We seek to cover: Python l
- Page 5 and 6: 1. Introduction Introductions Tutor
- Page 7 and 8: Why Use Python for Scientific Compu
- Page 9: Please login to the Tutorial Enviro
- Page 13 and 14: CPython Interpreter Notes Compilati
- Page 15 and 16: Built-in Numeric Types int, float,
- Page 17 and 18: Gotchas with Built-in Numeric Types
- Page 19 and 20: Built-in Sequence Types str, unicod
- Page 21 and 22: Built-in Sequence & Mapping Type Go
- Page 23 and 24: Control Structures for - iterative
- Page 25 and 26: List Comprehensions List Comprehens
- Page 27 and 28: File I/O Basics Most I/O in Python
- Page 29 and 30: Let's write ten integers to disk wi
- Page 31 and 32: Modules import - load module, defin
- Page 33 and 34: N-dimensional homogeneous arrays (n
- Page 35 and 36: Slicing Arrays >>> a = np.array([[1
- Page 37 and 38: SciPy Extends NumPy with common sci
- Page 39 and 40: Python Threading Python threads rea
- Page 41 and 42: Implementation Example: Calculating
- Page 43 and 44: Subprocess The subprocess module al
- Page 45 and 46: Calculating pi with multiprocessing
- Page 47 and 48: mpi4py wraps your native mpi prefer
- Page 49 and 50: from mpi4py import MPI import numpy
- Page 51 and 52: Python Best Practices for Performan
- Page 53 and 54: Outline a massively parallel Python
- Page 55 and 56: GPAW Strong-scaling Results
- Page 57 and 58: KS-DFT is a complex algorithm!
- Page 59 and 60: Performance Mantra People are able
- Page 61 and 62:
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
- Page 67 and 68:
Parallel Python Interpreter and Deb
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Profiling Mixed Python-C code Flat
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Python Interface to BLACS and ScaLA
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Python Interface to BLACS and ScaLA
- Page 75 and 76:
Python Interface to BLACS and ScaLA
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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
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Python for plotting and visualizati
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From Lib to App (overview) Numerica
- Page 89 and 90:
From Lib to App (overview) Storage
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Ruby on Rails Django TurboGears Pyl
- Page 93 and 94:
matplotlib gallery
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application1 application 2 applicat
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application 1 application=” dna
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web2py and Dispatching hostnam e
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web2py and Dispatching controller
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Upload DNA Seq. {{=form}} web2py a
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web2py and Authentication authentic
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web2py web based IDE web based IDE
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Before we start download web2py fro
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Define some algorithms def find_gen
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Define actions in controllers/defau
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Try it
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Define Actions in controllers/defau
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Try it
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Yet More Resources Tau http://www.c
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Let's review!
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This work is supported in part by t