[Numpy-discussion] Speed performance on array constant set
Christopher Barker
Chris.Barker at noaa.gov
Fri Jan 20 09:36:09 CST 2006
Sasha wrote:
>>python -m timeit -s "import numpy as na; a = na.zeros((1000,1000))" "a.fill(7)"
or use a += 7:
$ python2.4 -m timeit -s "import numpy as na; a =
na.zeros((1000,1000))" "a.fill(7)"
100 loops, best of 3: 6.95 msec per loop
$ python2.4 -m timeit -s "import numpy as na; a =
na.zeros((1000,1000))" "a += 7"
100 loops, best of 3: 3.24 msec per loop
A factor of 2 speedup for me. I don't know why fill is slower.
> So IPP gives me 3X, which leads me to ask about plans for IPP / SSE for
> NumPy, no offense intended to non Intel users.
I"ve wondered about this as as well, though not necessarily IPP / SEE.
It seems that BLAS should provide some optimizations that could be used
outside of the strictly linear algebra functions, like element-wise
multiplication, array copying, etc. However, I haven't looked into it,
and I suppose it would make for a lot of special-case code.
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
NOAA/OR&R/HAZMAT (206) 526-6959 voice
7600 Sand Point Way NE (206) 526-6329 fax
Seattle, WA 98115 (206) 526-6317 main reception
Chris.Barker at noaa.gov
More information about the Numpy-discussion
mailing list