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Re: [Discuss-gnuradio] CUDA GPU Vs CELL BE
From: |
Eric Blossom |
Subject: |
Re: [Discuss-gnuradio] CUDA GPU Vs CELL BE |
Date: |
Mon, 29 Jun 2009 21:28:00 -0700 |
User-agent: |
Mutt/1.5.18 (2008-05-17) |
On Mon, Jun 29, 2009 at 11:57:56PM -0400, Yu-Hua Yang wrote:
> Thanks
>
> 2009/6/29 Eric Blossom <address@hidden>
>
> > On Mon, Jun 29, 2009 at 05:21:29PM +0200, Vincenzo Pellegrini wrote:
> > > Hi everybody,
> > > I have recently had a look at two possibilities for SWRadio-aimed
> > intensive
> > > computing,
> > > which i guess are the two main development lanes for our kind of stuff:
> > >
> > > .:. Cell BE platform
> > > .:. CUDA & nVidia GPUs
> > >
> > > I think this list is the best place to for a discussion on PROs and CONs
> > of
> > > the two solutions,
> > > but couldn't find any by searching the mailing list.
> > >
> > > has this been discussed already?
> >
> > There's been a lot of conversation about this stuff, but mostly off list.
> >
> > Many of us are hoping that Larrabee turns out to be a big winner.
> >
> > The Cell BE is pretty cool, and fun to program, but I'm not sure how
> > much of a future it has.
> >
> > I'd say the court is still out on CUDA with regard to signal
> > processing applications. From my reading of the CUDA docs, it looks
> > like you need a very "data parallel" application to take good
> > advantage of it. Again from reading, it appears that you need at
> > least 64 elements that you can apply an instruction to, to be in it's
> > target zone. For certain parts of our graphs, this is probably OK
> > (e.g., FEC decode, FIR's, FFTs), but I'm kind of dubious about
> > anything with a depedency chain (IIR's, PLLs, equalizers, etc.)
>
>
> With regards to the 64 elements to apply an instruction to, can you say a
> bit more about this? Does it mean to at least a computation of than 64 times
> (like a loop thats more than 64 times) per one call to the device?
What little I know about CUDA is primarily based on reading this document:
http://developer.download.nvidia.com/compute/cuda/2_21/toolkit/docs/NVIDIA_CUDA_Programming_Guide_2.2.1.pdf
Eric