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Fri Jun 6 04:18:05 CEST 2014 · https://mail.python.org/pipermail/python-dev/2014-June/134839.html

On 05/06/14 22:51, Nathaniel Smith wrote:

> This gets evaluated as:
>
>     tmp1 = a + b
>     tmp2 = tmp1 + c
>     result = tmp2 / c
>
> All these temporaries are very expensive. Suppose that a, b, c are
> arrays with N bytes each, and N is large. For simple arithmetic like
> this, then costs are dominated by memory access. Allocating an N byte
> array requires the kernel to clear the memory, which incurs N bytes of
> memory traffic.

It seems to be the case that a large portion of the run-time in Python 
code using NumPy can be spent in the kernel zeroing pages (which the 
kernel does for security reasons).

I think this can also be seen as a 'malloc problem'. It comes about 
because each new NumPy array starts with a fresh buffer allocated by 
malloc. Perhaps buffers can be reused?

Sturla

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[Python-Dev] [numpy wishlist] Interpreter support for temporary elision in third-party classes