[Numpy-discussion] Unnecessarily bad performance of elementwise operators with Fortran-arrays

David Cournapeau david@ar.media.kyoto-u.ac...
Thu Nov 8 22:05:16 CST 2007


Travis E. Oliphant wrote:
> Christopher Barker wrote:
>> This discussion makes me wonder if the basic element-wise operations 
>> could (should?) be special cased for contiguous arrays, reducing them to 
>>   simple pointer incrementing from the start to the finish of the data 
>> block. The same code would work for C and Fortran order arrays, and be 
>> pretty simple.
>>
>> This would address Hans' issue, no?
>>
>> It's a special case but a common one.
>>
>>   
> There is a special case for this already.  It's just that the specific 
> operations he is addressing requires creation of output arrays that by 
> default are in C-order.    This would need to change in order to take 
> advantage of the special case.
For copy and array creation, I understand this, but for element-wise 
operations (mean, min, and max), this is not enough to explain the 
difference, no ? For example, I can understand a 50 % or 100 % time 
increase for simple operations (by simple, I mean one element operation 
taking only a few CPU cycles), because of copies, but a 5 fold time 
increase seems too big, no (mayb a cache problem, though) ? Also, the 
fact that mean is slower than min/max for both cases (F vs C) seems a 
bit counterintuitive (maybe cache effects are involved somehow ?).

Again, I see huge differences between my Xeon PIV @ 3.2 Ghz and my 
pentium M @ 1.2 Ghz for those operations: pentium M gives more 
"intuitive results (and is almost as fast, and sometimes even faster 
than my Xeon for arrays which can stay in cache).

cheers,

David



More information about the Numpy-discussion mailing list