[Numpy-discussion] Question about Optimization (Inline, and Pyrex)

James Turner jturner@gemini....
Tue Apr 17 14:55:09 CDT 2007


Hi Anne,

Your reply to Lou raises a naive follow-up question of my own...

> Normally, python's multithreading is effectively cooperative, because
> the interpreter's data structures are all stored under the same lock,
> so only one thread can be executing python bytecode at a time.
> However, many of numpy's vectorized functions release the lock while
> running, so on a multiprocessor or multicore machine you can have
> several cores at once running vectorized code.

Are you saying that numpy's vectorized functions will perform a single
array operation in parallel on a multi-processor machine, or just that
the user can explicitly write threaded code to run *multiple* array
operations on different processors at the same time? I hope that's not
too stupid a question, but I haven't done any threaded programming yet
and the answer could be rather useful...

Thanks a lot,

James.



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