I'm personally pessimistic about the STI Cell, but it's a reasonable example 
wrt the difficulty of writing the backends. Barring the data and message 
orchestration, which also aflicts GPUs, there's the decision function as to 
when to migrate a computation to the accelerator (GPU, SPU, ...) Not so much of 
a problem in chip symmetric mcore, but gets pretty dicey for hybrid mcore.

Been trying to wrap my head around that problem for a couple of years.

-scooter
Sent from my Verizon Wireless BlackBerry

-----Original Message-----
From: Jeff Heard <j...@renci.org>
Date: Wed, 3 Feb 2010 14:06:02 
To: Brad Larsen<brad.lar...@gmail.com>
Cc: GHC Users<glasgow-haskell-users@haskell.org>
Subject: Re: DPH and CUDA status

You're quite correct.  I should say supplant for normal uses.  The
OpenCL drivers are built on top of CUDA, and they intend CUDA to
continue to be available, but OpenCL is more portable and thus
something that we should probably target at some point.

On Wed, Feb 3, 2010 at 1:54 PM, Brad Larsen <brad.lar...@gmail.com> wrote:
> On Wed, Feb 3, 2010 at 12:34 PM, Jeff Heard <j...@renci.org> wrote:
>> [...]  One thing though, is that CUDA is being
>> supplanted by OpenCL in the next few years, and OpenCL can handle data
>> parallelism on multicore CPUs as well as GPUs with the same code.
>> It's a little more flexible overall than CUDA, and will be portable
>> across ATI/nVidia/Intell/AMD/Sony Cell in the end, and is well
>> supported on Linux, Mac, and Windows systems.
> [...]
>
> I have been told by NVIDIA folks that CUDA is not going to disappear.
> Its C++ API (as opposed to its ``driver interface'') is quite a bit
> higher level than OpenCL, suitable for (painful) application
> development, whereas OpenCL seems more targeted for compiler and
> framework writers.
>
> Sincerely,
> Brad
>
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