[fpc-devel] Parallel Computing

[Boian Mitov]

CUDA works best if you load the image and then perform multiple 
processing/transformations on it. This is the approach we take in our 
architecture.
CUDA uses task queue. It adds the tasks to the queue and assigns a core as 
soon as one is available. It uses some form of matrix for preparing the 
tasks.
The best approach IMHO is to use the CPU in a multithreaded filtering 
application to prepare the tasks, and add them to the queue, while the GPU 
just executes the tasks. then each CPU thread waits for its result while 
other threads are preparing the next set of data. This is the approach we 
take currently. In essence there is no timesharing in GPU Core. Each core 
will start working on a task and will not interrupt before completing it. 
This is different than a CPU MT. The standard MT is hardly needed when you 
have 240 cores in a single board, and you can join boards with external bus 
to share the queue ;-) . I think the current limit is 3 boards so you can 
scale up to 720 cores in a single system. I have only one board, but it is 
probably enough for me to do development.

With best regards,
  Boian Mitov

-------------------------------------------------------
Mitov Software
www.mitov.com
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----- Original Message ----- 
From: "Marco van de Voort" <marcov at stack.nl>
To: "FPC developers' list" <fpc-devel at lists.freepascal.org>
Sent: Tuesday, November 04, 2008 12:48 AM
Subject: Re: [fpc-devel] Parallel Computing


> Well, we stuff lighter cards (think 8500,8600) in our vision systems
> (passively cooled is better for factory use).
>
> We are also playing with CUDA, but one of the problems we have is that you
> must do pretty heavy transformations to earn back just the transfer of 
> data
> to and from videocard memory. Those are too rare for us to dive into that
> technology quickly, but I'm keeping notes :)
>
> However if one is more pattern recognition oriented, I can understand that
> it could get interesting.
>
> btw, is CUDA MT, as in that you can have several independant calculations 
> on
> the same GPU ?
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