RFC: naming for FrontTransversal and Transversal ranges

[Robert Jacques]

On Fri, 01 May 2009 21:14:54 -0400, Bill Baxter <wbaxter at gmail.com> wrote:

> On Fri, May 1, 2009 at 5:36 PM, bearophile <bearophileHUGS at lycos.com>  
> wrote:
>> Bill Baxter:
>>> Much more often the discussion on the numpy list takes the form of
>>> "how do I make this loop faster" becuase loops are slow in Python so
>>> you have to come up with clever transformations to turn your loop into
>>> array ops.  This is thankfully a problem that D array libs do not
>>> have.  If you think of it as a loop, go ahead and implement it as a
>>> loop.
>>
>> Sigh! Already today, and even more tomorrow, this is often false for D  
>> too. In my computer I have a cheap GPU that is sleeping while my D code  
>> runs. Even my other core sleeps. And I am using one core at 32 bits  
>> only.
>> You will need ways to data-parallelize and other forms of parallel  
>> processing. So maybe nornmal loops will not cuti it.
>
> Yeh.  If you want to use multiple cores you've got a whole 'nother can
> o worms.  But at least I find that today most apps seem get by just
> fine using a single core.  Strange though, aren't you the guy always
> telling us how being able to express your algorithm clearly is often
> more important than raw performance?
>
> --bb

Well, since I do GP-GPU work, the GPU algorithm is much algorithmically  
cleaner than the CPU algorithm. :) But I do know that this is very  
algorithm dependent.