[Insight-users] [Insight-developers] Cuda ITK

Thu Feb 12 20:00:20 EST 2009

Luis and all,

         I myself is not an expert in CUDA. But I will try to answer your 
question based on my understanding.

Different (NVIDIA) graphic card models have different numbers of 
multiprocessors and different amount of device memory. I guess a "good" CUDA 
code should be independent of those parameters. Our code (not written by me) 
probably is not a good one. Because when I ran it (written for GeForce 8800 
GTX) in my PC with GeForce 8500 GT, it failed. My student had to change some 
parameters so that I could run it successfully. But the efficiency was 
sacrificed.

Chen

----- Original Message ----- 
From: "Luis Ibanez" <luis.ibanez at kitware.com>
To: "Hua-Mei Chen" <huameichen0523 at gmail.com>
Cc: "Dan Mueller" <dan.muel at gmail.com>; "Gaëtan Lehmann" 
<gaetan.lehmann at jouy.inra.fr>; "Badri Roysam" <roysam at ecse.rpi.edu>; "ITK 
Users" <insight-users at itk.org>; "ITK Developers" 
<insight-developers at itk.org>
Sent: Thursday, February 12, 2009 4:32 PM
Subject: Re: [Insight-users] [Insight-developers] Cuda ITK

>
> Hi Chen,
>
>
> We have concerns about how GPU based implementations are
> strongly dependent on specific graphic card models and
> specific versions of the card drivers.
>
> Could you comment on the portability of your implementation ?
>
> Have you had a chance to run your systems in different
> models of the graphic card ?
>
> (and we understand that probably you have to be restricted
> to a familly of card from a specific vendor).
>
>
>
>
>    Thanks
>
>
>        Luis
>
>
> --------------------
> Hua-Mei Chen wrote:
>> 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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