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Hi Guys,
Just to chip in on the Quadro vs GeForce front. The Quadro cards are workstation level cards while the GeForce cards are gaming cards. So what does that mean? Well the Quadro will sometimes have more RAM (though nowadays not as often), a potential faster memory interface/bandwidth and a 3 year full support warranty. It is generally the extended warranty and support you are paying for.
For standard 3D rendering in Imaris, AutoQuant, Huygens etc you will find that a high end gaming card with a large amount (1-2GB) of RAM will perform identically to the equivalent Quadro card. Except the quadro card will cost you many times more to purchase.
Now one problem you can hit is if you are buying a preconfigured workstation from someone like HP or Dell. As it is a workstation, it will come with a workstation card in it. The upgrades offered are usually to higher level Quadro cards for a decent cost. You can leave the base level card in it and upgrade it yourself later (providing it doesn't void warranty and that the power supply in the system can handle the load).
Cheers
Cam
Cameron J. Nowell
Microscopy Manager
Centre for Advanced Microscopy
Ludwig Institute for Cancer Research Melbourne - Parkville Branch
PO Box 2008
Royal Melbourne Hospital
Victoria, 3050
AUSTRALIA
Office: +61 3 9341 3158
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-----Original Message-----
From: Confocal Microscopy List [mailto:[log in to unmask]] On Behalf Of G. Esteban Fernandez
Sent: Wednesday, 28 March 2012 10:00 AM
To: [log in to unmask]
Subject: Re: Grfx cards for AutoQuant/AutoDeblur
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Thanks for the input everyone. I'll stick with NVIDIA. My IT dept.
went for the same GTX580 that worked well for Brian.
Interesting that according to MediaCy said they don't use CUDA for decon., only for rendering....
-Esteban
On Tue, Mar 27, 2012 at 3:03 PM, Tim Holmes <[log in to unmask]> wrote:
> *****
> To join, leave or search the confocal microscopy listserv, go to:
> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
> *****
>
> Thanks Guy .... yes, but to clarify I don't really know what they did
> to get it working so fast with the GPU's. Andy corrected my posting.
> That GPU work was all done by the Media Cy engineers after they took
> over the development of AutoDeblur/AutoQuant. People who have used it
> have told me that the deconvolution runs very fast now thanks to those improvements.
>
> Regards
> Tim
>
> -----Original Message-----
> From: Confocal Microscopy List
> [mailto:[log in to unmask]] On Behalf Of Guy Cox
> Sent: Tuesday, March 27, 2012 4:05 PM
> To: [log in to unmask]
> Subject: Re: Grfx cards for AutoQuant/AutoDeblur
>
> *****
> To join, leave or search the confocal microscopy listserv, go to:
> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
> *****
>
> Just in case some folks on the list don't realise, Tim is the original
> author of the Autoquant / Autodeblur software, even though he is now
> no longer connected with it.
>
> Guy
>
> -----Original Message-----
> From: Confocal Microscopy List
> [mailto:[log in to unmask]] On Behalf Of Tim Holmes
> Sent: Wednesday, 28 March 2012 3:57 AM
> To: [log in to unmask]
> Subject: Re: Grfx cards for AutoQuant/AutoDeblur
>
> *****
> To join, leave or search the confocal microscopy listserv, go to:
> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
> *****
>
> Esteban,
>
> We have experience in using NVIDIA Cuda cards in software development
> projects in other areas, like computed tomography. At least in our
> case, for our projects, you HAVE to use NVIDIA because they are the
> only ones that are CUDA compatible. CUDA is the language used to
> program the cards that gives them the "parallel processing"
> capability. At least in our case, for our projects, we automatically
> detect if the NVIDIA card is there and if it is CUDA compatible.
> Then, if so, we execute the algorithms on the cards rather than the
> CPU. If any other card is there, besides and NVIDIA CUDA card, then
> we execute the algorithms on the slower CPU. I can't speak for the
> Media Cybernetics product, but I would guess (not really knowing) that
> they must do soething along those lines. If so, you would only get
> the speed advantage with an NVIDIA CUDA compatible card. Other cards,
> like ATI Radeon, have their own languages they use fore speeding up graphics which are not CUDA. That's why they don't work for CUDA programs.
>
> I am not working for Media Cybernetics, and I do not know if this
> would be their official answer from their support group. I am
> guessing what the answer would be based on our experience using CUDA
> and NVIDIA cards in other projects.
>
> Tim Holmes, D.Sc.
> CEO
> Lickenbrock Technologies, LLC
>
> -----Original Message-----
> From: Confocal Microscopy List
> [mailto:[log in to unmask]] On Behalf Of G. Esteban
> Fernandez
> Sent: Tuesday, March 27, 2012 11:20 AM
> To: [log in to unmask]
> Subject: Grfx cards for AutoQuant/AutoDeblur
>
> *****
> To join, leave or search the confocal microscopy listserv, go to:
> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
> *****
>
> Hi all,
>
> I'm purchasing a new computer to be used for deconvolving confocal
> data with Media Cybernetics's AutoQuant/AutoDeblur software (ver.
> X1.4.1 maybe upgrading to X3). I know MediaCy recommends NVIDIA
> graphics cards for their CUDA parallel processing ability but my
> computer people want to purchase a different card, ostensibly because
> we get a deal on the particular brand they want. The card (GIGABYTE
> GV-R797D5-3GD-B) does have parallel processors but they're not branded
> as CUDA, I don't know enough to determine if that makes a difference;
> it does support openGL. I'd appreciate it if people would share their
> experiences running AutoDeblur with non-NVIDIA (non-CUDA) cards.
>
> Thanks,
> Esteban
>
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