[Insight-developers] [Insight-users] Coda ITK

Fri Feb 13 15:57:11 EST 2009

Why does cuda now work well with the ITK pipeline?

On Feb 13, 2009, at 3:43 PM, Daniel Blezek wrote:

> My lab currently makes heavy use of acceleration on the Cell, and we  
> are
> looking to do more with CUDA (hopefully OpenCL as it matures).  Our  
> take is
> that accelerated code works best next to, and not inside ITK.  For  
> instance,
> run an ITK pipeline, grab the output into some CUDA code, process  
> using
> CUDA, then back into ITK.  This paradigm works quite well, though  
> you'll
> have to manage the pipeline updates manually.
>
> This way ITK is used for what it's best at, and CUDA/OpenCL is used  
> for what
> it's best at.
>
> $0.02,
> -dan
>
>
> On 2/12/09 2:19 PM, "Hua-Mei Chen" <huameichen0523 at gmail.com> wrote:
>
>> I have seen several discussions on this issue before in this  
>> emailing list.
>>
> My impression is that it is not possible or very difficult to  
> combine CUDA
>>
> and ITK for now. All I can say is that CUDA indeed is able to give  
> you a
>>
> significant speedup, but it strongly depends on the quality of your  
> CUDA
>>
> codes.
>
> Chen
>
>
> ----- Original Message -----
> From: "Marcel Weiss"
>> <mweiss at cbs.mpg.de>
> To: "Hua-Mei Chen" <huameichen0523 at gmail.com>
> Cc:
>> <insight-users at itk.org>; <insight-developers at itk.org>
> Sent: Thursday, February
>> 12, 2009 11:06 AM
> Subject: Re: [Insight-developers] [Insight-users] Cuda
>> ITK
>
>
> As we ordered a new number crunching machine including a NVIDIA  
> Tesla TM
>>
> C1060 and we are planning to use it for the fast processing of our
>>
> high-resolition 3D images, I´d be interested in some more statements  
> and
>>
> experiences on CUDA (pure and/or with ITK).
>
> Would you suggest planning and
>> programming new code or adjusting existing
> code?
> I´m sure there is a tradeoff
>> between man power needed and speed-up gained
> ...
>
> Marcel
>> Weiss
> Dipl.-Inf.(FH)
> PhD student
> Department of Neurophysics
> Max Planck
>> Institute for Human Cognitive and Brain Sciences
>
> ----- Original Message
>> -----
> From: "Hua-Mei Chen" <huameichen0523 at gmail.com>
> To: "Dan Mueller"
>> <dan.muel at gmail.com>, "Gaëtan Lehmann"
> <gaetan.lehmann at jouy.inra.fr>, "Badri
>> Roysam" <roysam at ecse.rpi.edu>
> Cc: "ITK Users" <insight-users at itk.org>, "ITK
>> Developers"
> <insight-developers at itk.org>
> Sent: Thursday, February 12, 2009
>> 5:21:11 PM GMT +01:00 Amsterdam / Berlin /
> Bern / Rome / Stockholm /
>> Vienna
> Subject: Re: [Insight-developers] [Insight-users]  Cuda ITK
>
> Well, we
>> wrote some PURE CUDA code for our mutual information based
> non-rigid
>> registration. It did give us a significant (> 100 times for some
> routines)
>> speedup. But I have no idea how to use it with ITK.
>
> Chen
>
>
> ----- Original
>> Message -----
> From: "Badri Roysam" <roysam at ecse.rpi.edu>
> To: "Dan Mueller"
>> <dan.muel at gmail.com>; "Gaëtan Lehmann"
> <gaetan.lehmann at jouy.inra.fr>
> Cc: "ITK
>> Users" <insight-users at itk.org>; "ITK
>> Developers"
> <insight-developers at itk.org>
> Sent: Thursday, February 12, 2009
>> 8:50 AM
> Subject: Re: [Insight-users] [Insight-developers] Cuda ITK
>
>
> We
>> invested heavily in GPUs and CUDA in my lab a couple of years ago.
>> Our
> practical
> experience has been that these things don't work quite as we had
>> imagined
> from the
> advertising. In other words, when we compiled our vessel
>> segmentation codes
> on CUDA,
> we found no speedup (in some case, it was slower
>> than optimized compilation
> on the CPU.
> It took a lot of work to get speedup
>> over serial code. You have to rethink
> your
> code to suit a streaming
>> architecture, and spend time working out the data
> flows carefully.
> Overall, we
>> learned that the effort involved in building
> "GPU versions" of existing
>> routines is
> manpower intensive. I am interested to know what others'
>> experience has
> been.
>
>
> Badri Roysam
> Professor, Department of Electrical,
>> Computer and Systems Engineering
> Associate Director, NSF Center for Subsurface
>> Sensing & Imaging Systems
> (CenSSIS ERC)
> Co-Director, Rensselaer Center for
>> Open Source Software
> Rensselaer Polytechnic Institute
> 110 8th Street, Troy,
>> New York 12180-3590, USA.
> Office(JEC 7010): 518-276-8067, Assistant:
>> 518-276-8525, Lab(JEC 6308):
> 518-276-8207, Fax: 518-276-8715
> Email:
>> roysam at ecse.rpi.edu, Web: http://www.ecse.rpi.edu/~roysam
>
>
>
> ----- Original
>> Message -----
> From: Dan Mueller [mailto:dan.muel at gmail.com]
> To: Gaëtan Lehmann
>> [mailto:gaetan.lehmann at jouy.inra.fr]
> Cc: ITK Users
>> [mailto:insight-users at itk.org], ITK
>> Developers
> [mailto:insight-developers at itk.org]
> Subject: Re: [Insight-users]
>> [Insight-developers] Cuda ITK
>
>
>> Hi Gaetan,
>>
>> I too have been following the
>> closely development of the GPGPU field
>>
>> http://en.wikipedia.org/wiki/Gpgpu
>> and waiting for ITK to jump on board
>> (unfortunately I have had little
>> spare time to spearhead this myself).
>>
>> I
>> remember speaking to Luis at a t-con last year about ITK+CUDA and he
>>
>> mentioned one of outcomes of the project was discovering that CUDA is
>> not
>> (yet) very portable (i.e. code that works on one NVIDIA card, does
>> not
>> necessarily work on another).
>>
>> If ITK is going to be GPGPU-enabled, then
>> perhaps the OpenCL standard
>> will provide more portability:
>>
>> http://en.wikipedia.org/wiki/OpenCL
>>
>> Obviously OpenCL is still new (version
>> 1.0 approved December 8, 2008),
>> but I imagine we'll start seeing supporting
>> hardware soon
>>    http://www.nvidia.com/object/io_1228825271885.html
>>
>>
>> http://news.softpedia.com/news/AMD-Takes-Up-OpenCL-1-0-Puts-More-Effort-on-ATI
>> -Stream-SDK-99578.shtml
>> and maybe even Intel's Larrabee
>>
>> http://www.hpcwire.com/blogs/OpenCL_On_the_Fast_Track_33608199.html
>>
>> (I
>> don't think NVIDIA or ATI has to date officially announced a chip
>> with
>> OpenCL support...I'd be happy to be proved wrong...)
>>
>> Because much of this
>> is still speculative, it doesn't really factor
>> into your discussion about
>> what hardware to buy today... Just a
>> warning: while CUDA is the pioneer, it
>> may not be be around to see the
>> real action.
>>
>> Cheers, Dan
>>
>> 2009/2/11
>> Gaëtan Lehmann <gaetan.lehmann at jouy.inra.fr>:
>>>
>>> Hi,
>>>
>>> We are
>> currently thinking to buy a few powerful workstations to run ITK
>>> in
>>> my
>> lab.
>>> I heard of nvidia's tesla cards, and I see that some experiments
>> has
>>> been
>>> made to use them in ITK.
>>>
>>>
>> http://www.na-mic.org/Wiki/images/f/f9/Itk-gpu-meeting-Fall2007.ppt
>>>
>>> Is
>> there any update since fall 2007?
>>>
>>> Regards,
>>>
>>> Gaëtan
>>>
>>>
>>>
>> --
>>> Gaëtan Lehmann
>>> Biologie du Développement et de la Reproduction
>>>
>> INRA de Jouy-en-Josas (France)
>>> tel: +33 1 34 65 29 66    fax: 01 34 65 29
>> 09
>>> http://voxel.jouy.inra.fr  http://www.mandriva.org
>>>
>> http://www.itk.org  http://www.clavier-dvorak.org
>>
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========================================================
Bradley Lowekamp
Lockheed Martin Contractor for
Office of High Performance Computing and Communications
National Library of Medicine
blowekamp at mail.nih.gov

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