[Numpy-discussion] Back to numexpr

Tim Hochberg tim.hochberg at cox.net
Tue Jun 13 12:03:54 CDT 2006


Oops! Having just done an svn update, I now see that David appears to 
have done most of this about a week ago...

I'm behind the times.

-tim

Tim Hochberg wrote:

>I've finally got around to looking at numexpr again. Specifically, I'm 
>looking at Francesc Altet's numexpr-0.2, with the idea of harmonizing 
>the two versions. Let me go through his list of enhancements and comment 
>(my comments are dedented):
>
>    - Addition of a boolean type. This allows better array copying times
>    for large arrays (lightweight computations ara typically bounded by
>    memory bandwidth).
>
>Adding this to numexpr looks like a no brainer. Behaviour of booleans 
>are different than integers, so in addition to being more memory 
>efficient, this enables boolean &, |, ~, etc to work properly.
>
>    - Enhanced performance for strided and unaligned data, specially for
>    lightweigth computations (e.g. 'a>10'). With this and the addition of
>    the boolean type, we can get up to 2x better times than previous
>    versions. Also, most of the supported computations goes faster than
>    with numpy or numarray, even the simplest one.
>
>Francesc, if you're out there, can you briefly describe what this 
>support consists of? It's been long enough since I was messing with this 
>that it's going to take me a while to untangle NumExpr_run, where I 
>expect it's lurking, so any hints would be appreciated.
>
>    - Addition of ~, & and | operators (a la numarray.where)
>
>Sounds good.
>
>    - Support for both numpy and numarray (use the flag --force-numarray
>    in setup.py).
>
>At first glance this looks like it doesn't make things to messy, so I'm 
>in favor of incorporating this.
>
>    - Added a new benchmark for testing boolean expressions and
>    strided/unaligned arrays: boolean_timing.py
>
>Benchmarks are always good.
>
>    Things that I want to address in the future:
>
>    - Add tests on strided and unaligned data (currently only tested
>    manually)
>
>Yep! Tests are good.
>
>    - Add types for int16, int64 (in 32-bit platforms), float32,
>      complex64 (simple prec.)
>
>I have some specific ideas about how this should be accomplished. 
>Basically, I don't think we want to support every type in the same way, 
>since this is going to make the case statement blow up to an enormous 
>size. This may slow things down and at a minimum it will make things 
>less comprehensible. My thinking is that we only add casts for the extra 
>types and do the computations at high precision. Thus adding two int16 
>numbers compiles to two OP_CAST_Ffs followed by an OP_ADD_FFF, and then 
>a OP_CAST_fF.  The details are left as an excercise to the reader ;-). 
>So, adding int16, float32, complex64 should only require the addition of 
>6 casting opcodes plus appropriate modifications to the compiler.
>
>For large arrays, this should have most of the benfits of giving each 
>type it's own opcode, since the memory bandwidth is still small, while 
>keeping the interpreter relatively simple.
>
>Unfortunately, int64 doesn't fit under this scheme; is it used enough to 
>matter? I hate pile a whole pile of new opcodes on for something that's 
>rarely used.
>
>
>Regards,
>
>-tim
>
>
>
>
>
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