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Define 'prefetching' for users

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Juan Nunez-Iglesias
2014-12-31 17:07:28 +11:00
parent b998405f48
commit 76103d4b05
1 changed files with 3 additions and 2 deletions
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doc/source/user_guide/numpy_images.txt
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@@ -156,8 +156,9 @@ Notes on array order
Although the labeling of the axes seems arbitrary, it can have a
significant effect on speed of operations. This is because modern
processors never retrieve just one item from memory, but rather a
whole chunk of adjacent items. Therefore, processing elements that are
adjacent in memory one after the other is faster than processing them
whole chunk of adjacent items. (This is called prefetching.)
Therefore, processing elements that are
next to each other in memory is faster than processing them
in a different order, even if the number of operations is the same:
>>> def in_order_multiply(arr, scalar):