High Performance Python tutorial v0.2

The goal is to take you on several journeys which show you different ways of making Python code run much faster (up to 75* on the CPU, faster with a GPU).

Topics covered:
Python profiling (cProfile, RunSnake, line_profiler) – find bottlenecks
PyPy – Python’s new Just In Time compiler, a note on the new numpy module
Cython – annotate your code and compile to C
numpy integration with Cython – fast numerical Python library wrapped by Cython
ShedSkin – automatic code annotation and conversion to C
numpy vectors – fast vector operations using numpy arrays
NumExpr on numpy vectors – automatic numpy compilation to multiple CPUs and vector units
multiprocessing – built-in module to use multiple CPUs
ParallelPython – run tasks on multiple computers
pyCUDA – run tasks on your Graphics Processing Unit
Other algorithmic choices and options you have

: http://ianozsvald.com/2011/07/25/high-performance-python-tutorial-v0-2-from-europython-2011/