[AstroPy] Image combine
Derek Homeier
derek at astro.physik.uni-goettingen.de
Wed Mar 7 10:40:32 EST 2012
On 7 Mar 2012, at 16:17, Perry Greenfield wrote:
> Do you have any good example of code like this is successfully
> distributed to users in the wild? So far, the dependencies on the
> specific GPU hardware seem to make this impractical right now. But
> maybe I'm missing something.
>
> And I'm also a bit confused by the first statement. Are you arguing
> that we should be porting SPP to GPUs?
I'd agree that optimisation is an important issue; enabling GPU is one part of that,
classical parallelisation (multi-core/shared memory first) another part.
But these are rather two sides of the medal; if the basic tasks are not available
people will not be willing or even able to switch from IRAF or other suites.
The best perspectives for speed-ups OTOH lie most likely in the underlying
routines, i.e. for the most part the numpy core routines or even below (like the
general-purpose numeric libraries numpy or scipy are calling), and that is
where any optimisation effort is best spent - just my 2p.
Cheers,
Derek
> On Mar 7, 2012, at 10:11 AM, Tiago Ribeiro de Souza wrote:
>
>> Hi guys,
>>
>> Even though I understand that people want to be free from using
>> IRAF, I don't agree that only translating its basic functionality
>> to other programming language is actually useful. If we ought to
>> look to the future I would say that we should start an effort to
>> provide a GPU-enabled suite of image reduction facility ratter than
>> replicating existing code in different languages. Given the level of
>> paralalization of image reduction (say image combine, subtraction,
>> division, source extraction, spectral extraction and more!) GPU
>> programming will definitively be much more important and useful.
>>
>> For those who are interested, check out this tutorial at http://www.macresearch.org/opencl
>> and http://developer.nvidia.com/content/september-2009-opencl-public-downloads
>
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