Grfx cards for AutoQuant/AutoDeblur

[G. Esteban Fernandez]

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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

[Craig Brideau]

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Shouldn't Gigabyte or Nvidia be able to tell you if they will work?  Try
dropping them an email to be sure.  You don't want to end up with a card
you can't use for the sake of trying to save a few bucks...

Craig

On Tue, Mar 27, 2012 at 10:19 AM, G. Esteban Fernandez <
[hidden email]> wrote:

> *****
> 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
>

[Tim Holmes]

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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:[hidden email]] On
Behalf Of G. Esteban Fernandez
Sent: Tuesday, March 27, 2012 11:20 AM
To: [hidden email]
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

-----
No virus found in this message.
Checked by AVG - www.avg.com
Version: 2012.0.1913 / Virus Database: 2114/4897 - Release Date: 03/27/12

[Peter Humphreys]

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Minimum requirements for Autoquants software are an NVIDIA graphics card,

the Gigabyte card is an ATI based card, so it is not likely to work well
for the visualisation if thats important (specific shaders i think). I
believe CUDA is NVIDIA's API for GPU processing, (too many acronyms) so
that is not going to be available.
The cost can't be that great a difference to justify hobbling your
application.

Peter

> *****
> 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

[Guy Cox-2]

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*****

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:[hidden email]] On Behalf Of Tim Holmes
Sent: Wednesday, 28 March 2012 3:57 AM
To: [hidden email]
Subject: Re: Grfx cards for AutoQuant/AutoDeblur

*****
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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:[hidden email]] On Behalf Of G. Esteban Fernandez
Sent: Tuesday, March 27, 2012 11:20 AM
To: [hidden email]
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

-----
No virus found in this message.
Checked by AVG - www.avg.com
Version: 2012.0.1913 / Virus Database: 2114/4897 - Release Date: 03/27/12

[Armstrong, Brian]

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*****

That is good to know.
I recently was advised to purchase a Graphics card for our 3D rendering software. It was recommended we get the NVidia Quadro FX. Our ITS Dept said "no, it's too expensive". We compromised on an NVidia GeForce GTX580 (not too expensive). We use Media Cybernetics / Autoquant X Gold v.X2.2.2, and have had good success with this card.
Perhaps you (Esteban) could come to a similar compromise with your IT Group?

Brian Armstrong PhD
Assistant Research Professor
Light Microscopy Core
Beckman Research Institute
City of Hope
1500 East Duarte Road
Duarte, CA 91010
626-256-4673 x62872

Light Microscopy Core Facility

-----Original Message-----
From: Confocal Microscopy List [mailto:[hidden email]] On Behalf Of Guy Cox
Sent: Tuesday, March 27, 2012 2:05 PM
To: [hidden email]
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:[hidden email]] On Behalf Of Tim Holmes
Sent: Wednesday, 28 March 2012 3:57 AM
To: [hidden email]
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:[hidden email]] On Behalf Of G. Esteban Fernandez
Sent: Tuesday, March 27, 2012 11:20 AM
To: [hidden email]
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

-----
No virus found in this message.
Checked by AVG - www.avg.com
Version: 2012.0.1913 / Virus Database: 2114/4897 - Release Date: 03/27/12


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[Tim Holmes]

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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:[hidden email]] On
Behalf Of Guy Cox
Sent: Tuesday, March 27, 2012 4:05 PM
To: [hidden email]
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:[hidden email]] On
Behalf Of Tim Holmes
Sent: Wednesday, 28 March 2012 3:57 AM
To: [hidden email]
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:[hidden email]] On
Behalf Of G. Esteban Fernandez
Sent: Tuesday, March 27, 2012 11:20 AM
To: [hidden email]
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

-----
No virus found in this message.
Checked by AVG - www.avg.com
Version: 2012.0.1913 / Virus Database: 2114/4897 - Release Date: 03/27/12

-----
No virus found in this message.
Checked by AVG - www.avg.com
Version: 2012.0.1913 / Virus Database: 2114/4897 - Release Date: 03/27/12

[G. Esteban Fernandez]

*****
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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
<[hidden email]> 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:[hidden email]] On
> Behalf Of Guy Cox
> Sent: Tuesday, March 27, 2012 4:05 PM
> To: [hidden email]
> 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:[hidden email]] On
> Behalf Of Tim Holmes
> Sent: Wednesday, 28 March 2012 3:57 AM
> To: [hidden email]
> 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:[hidden email]] On
> Behalf Of G. Esteban Fernandez
> Sent: Tuesday, March 27, 2012 11:20 AM
> To: [hidden email]
> 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
>
> -----
> No virus found in this message.
> Checked by AVG - www.avg.com
> Version: 2012.0.1913 / Virus Database: 2114/4897 - Release Date: 03/27/12
>
> -----
> No virus found in this message.
> Checked by AVG - www.avg.com
> Version: 2012.0.1913 / Virus Database: 2114/4897 - Release Date: 03/27/12

[Cameron Nowell]

*****
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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: [phone]
Mobile: [phone]
Fax: [phone]
Facility Website
Linked In Profile



-----Original Message-----
From: Confocal Microscopy List [mailto:[hidden email]] On Behalf Of G. Esteban Fernandez
Sent: Wednesday, 28 March 2012 10:00 AM
To: [hidden email]
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
*****

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 <[hidden email]> 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:[hidden email]] On Behalf Of Guy Cox
> Sent: Tuesday, March 27, 2012 4:05 PM
> To: [hidden email]
> 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:[hidden email]] On Behalf Of Tim Holmes
> Sent: Wednesday, 28 March 2012 3:57 AM
> To: [hidden email]
> 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:[hidden email]] On Behalf Of G. Esteban
> Fernandez
> Sent: Tuesday, March 27, 2012 11:20 AM
> To: [hidden email]
> 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
>
> -----
> No virus found in this message.
> Checked by AVG - www.avg.com
> Version: 2012.0.1913 / Virus Database: 2114/4897 - Release Date:
> 03/27/12
>
> -----
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> Checked by AVG - www.avg.com
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The views expressed in this communication are those of the sender and do not necessarily reflect the views of the Ludwig Institute for Cancer Research Ltd.

[Cameron Nowell]

*****
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*****

I would have thought rendering would have been done in OpenGL/AL, DirectX etc as those are the APIs used for rendering. All maths processing/parallel number crunching would go through CUDA.



-----Original Message-----
From: Confocal Microscopy List [mailto:[hidden email]] On Behalf Of G. Esteban Fernandez
Sent: Wednesday, 28 March 2012 10:00 AM
To: [hidden email]
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
*****

*****
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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 <[hidden email]> 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:[hidden email]] On Behalf Of Guy Cox
> Sent: Tuesday, March 27, 2012 4:05 PM
> To: [hidden email]
> 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:[hidden email]] On Behalf Of Tim Holmes
> Sent: Wednesday, 28 March 2012 3:57 AM
> To: [hidden email]
> 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:[hidden email]] On Behalf Of G. Esteban
> Fernandez
> Sent: Tuesday, March 27, 2012 11:20 AM
> To: [hidden email]
> 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
>
> -----
> No virus found in this message.
> Checked by AVG - www.avg.com
> Version: 2012.0.1913 / Virus Database: 2114/4897 - Release Date:
> 03/27/12
>
> -----
> No virus found in this message.
> Checked by AVG - www.avg.com
> Version: 2012.0.1913 / Virus Database: 2114/4897 - Release Date:
> 03/27/12

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This communication is intended only for the named recipient and may contain information that is confidential, legally privileged or subject to copyright; the Ludwig Institute for Cancer Research Ltd does not waive any rights if you have received this communication in error.
The views expressed in this communication are those of the sender and do not necessarily reflect the views of the Ludwig Institute for Cancer Research Ltd.