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Hello,
Actually I was thinking about it more than a year ago
when I accidentially read about someone doing sound processing
on nVidia GPU.
At that time several problems were present
and some of them are valid upto this date.
Mainly:
- only recent GPUs have fully programmable shaders and not everyone
has very recent card
- great speed increases could be achieved only when running really
long data sets and I am not sure if say 10 year of EOD data (2600 data points)
is long enough to see significant improvement
- code needs to be written for specific GPU (different for nVidia and different for ATI)
But - yes it is interesting area to investigate.
Best regards,
Tomasz Janeczko
amibroker.com
----- Original Message -----
From: "b" <b519b@xxxxxxxxx>
To: <amibroker@xxxxxxxxxxxxxxx>
Sent: Sunday, October 09, 2005 6:32 AM
Subject: [amibroker] OT: math speed increase of using GUPs (for Tomasz)
> Thomasz:
>
> I know you very forward looking -- your array processing
> approach in Amibroker shows that. So you might be
> interested to see how some Stanford academics are using
> GPUs from ATI and nVidia to do "fuzzy" logic calculations
> with protein comparisions.
>
> I would not be surprised to see you find a way to use the
> "streaming" code of graphic chips to give Amibroker the
> same outstanding speed in genetic optimization that
> Amibroker now achieves with regular optimizations using
> array processing.
>
> Here is the URL for the Stanford paper:
> http://graphics.stanford.edu/papers/clawhmmer/hmmer.pdf
>
> That article is a bit of heavy reading (specialized code
> sequences for protein comparisons), but I could figure
> enough out to see that the general approach reminds me a
> bit of the role that "Math co-processors" used to have
> years ago when CPU had limited internal math ability.
>
> Here is a URL that gives a summary:
> http://www.tgdaily.com/2005/10/07/stanford_gpgpu/
>
> b
>
>
>
>
>
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