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Holger Schurig wrote:
<blockquote cite="mid200501200919.40654.hs4233@mail.mn-solutions.de"
type="cite">
<blockquote type="cite">
<pre wrap="">Does anybody out there have the know-how and time to lead (or at least
help get some of us started)
</pre>
</blockquote>
<pre wrap=""><!---->
I don't have know-how, but there are several web site that have the know
how, e.g.
<a class="moz-txt-link-freetext" href="http://www.shadertech.com/">http://www.shadertech.com/</a>
I also know that on SF.NET there is a project of a hardware-gnostic GPU
programming language with compiler towards various GPUs, but I forgot the
name.
</pre>
</blockquote>
<br>
That would be libsh, which Nick mentioned already :)<br>
<br>
I think that there still probably needs to be some research done to see
how much this might help; i.e. is there going to be a lot of latency or
overhead in moving data to/from the GPU, and making things happen?<br>
<br>
One characteristic of what we're trying to do here is that, for
translators, we're performing lots of operations (encode/decode) on
very small data sets; So, in most cases, the encode operation might be:<br>
<br>
1) copy 20ms of PCM audio to GPU-accessible memory (unless it can
access main memory?)<br>
2) Call the GPU routines.<br>
3) The GPU does the encoding.<br>
4) Wait for the GPU to complete.<br>
5) copy back the encoded 20ms data.<br>
<br>
As opposed to the Primary CPU equivalent:<br>
C1) The CPU does the encoding.<br>
<br>
This needs to be done 50 times/sec/call...<br>
<br>
So, while (3) might be much faster than C1, 1+2+3+4+5 might not..<br>
<br>
Of course, there may be ways to alleviate this, like coding many calls
together or something, to exploit the GPU parallelism, etc, but there's
still a real possibility that this might not be a win at all..<br>
<br>
Certainly an interesting research project, though.<br>
<br>
-SteveK<br>
<br>
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