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I second Craig's comment on SSD PCI-e card speed. I have several such
cards in my core's PC's, also some of their SSD SATA drives. One problem
with all SSD's is when they die, that's it" everything is lost. Back it
up or expect to lose it. Don't count on achieving the specifications
provided by OCZ (or any other vendor) - operating system driver
performance may be limiting.
On 3/10/2013 2:30 PM, Craig Brideau wrote:
> *****
> To join, leave or search the confocal microscopy listserv, go to:
> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
> *****
>
> As Oliver says, an SSD can help speed things along. You can get PCI-e
> cards which are SSD's rather than relying on the SATA bus for data
> transfer. They can be quite speedy depending on what you are doing:
>
> http://www.ocztechnology.com/products/solid_state_drives/pci-e_solid_state_drives
>
> I use one of these in our image acquisition computers tied to one of our
> microscopes. It makes file writes for large image stacks go much faster
> than a mechanical drive.
>
> Craig
>
>
>
> On Sun, Mar 10, 2013 at 12:28 AM, Oliver Biehlmaier<
> [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
>> *****
>>
>> Yes, that is the correct order. At least for the software that we are
>> using the CPU speed is the most important.
>> The SSD for the OS and swapping (eg in Imaris) is also an important point
>> for speed.
>> Cheers,
>> Oliver
>>
>>
>>>
>>> ------------------------------
>>>
>>> Date: Sat, 9 Mar 2013 05:56:27 -0500
>>> From: "Watkins, Simon C"<[log in to unmask]>
>>> Subject: Re: Subject: Computer for image analysis
>>>
>>> *****
>>> To join, leave or search the confocal microscopy listserv, go to:
>>> http://lists.umn.edu/cgi-bin/wa?A0=3Dconfocalmicroscopy
>>> *****
>>>
>>> So Oliver, what you are saying is that the ultimate bottleneck is the CPU
>>> speed, followed by RAM, followed by CPU core count and finally graphics
>>> card capabilities?
>>>
>>> Simon Watkins Ph.D
>>>
>>> Professor and Vice Chair Cell Biology
>>> Professor Immunology
>>> Director Center for Biologic Imaging
>>> University of Pittsburgh
>>> Bsts 225 3550 terrace st
>>> Pittsburgh PA 15261
>>> Www.cbi.pitt.edu<http://Www.cbi.pitt.edu/>
>>> 412-352-2277
>>>
>>>
>>>
>>>
>>>
>>>
>>> On 3/9/13 3:39 AM, "Oliver Biehlmaier"<[log in to unmask]>
>>>
>> wrote:
>>
>>>
>>>> Dear Arvydas,
>>>> I equipped an entire image analysis room with new Image analysis
>>>>
>> machines
>>
>>>> about 1.5 years ago. During the evaluation, our main focus was on the
>>>> system's performance using software such as Imaris, Volocity, Huygens,
>>>> Fiji, etc.
>>>> As already posted in other replies to your email it turns out that GPU
>>>>
>> is
>>
>>>> important, but bottlenecks are CPU, RAM, and the speed of the HDD.
>>>> As our institute's IT asked us to go for a Dell-solution, we evaluated
>>>> several possibilities from Dell. We ended up buying 2 Dell Precision
>>>>
>> with
>>
>>>> 3GB-GPU, XEON-processors and between 24 to 48GB of RAM, and many
>>>>
>> "pimped"
>>
>>>> Optiplex systems where we installed 3GB-GPU, the max. RAM (16GB), an SSD
>>>> for the OS and swapping and a fast 500GB-HDD for saving the data.
>>>> Price wise the Optiplex systems sum up to a third of the price of the
>>>> precision.
>>>> The main reason for the Optiplex was the i7 processor which is capable
>>>>
>> to
>>
>>>> do overclocking which is not possible on the XEON systems. We expected
>>>> this to be a key advantage in comparison to our expensive Precision
>>>> systems.
>>>> Now, after 1,5 years of usage I can confirm that this fully worked out.
>>>> As many programs (especially Imaris) are still mainly relying on only
>>>>
>> one
>>
>>>> but definitely not on all cores, the overclocking feature of the i7
>>>> system usually keeps them at the same level or even outperforms the
>>>> Precision systems. Only the 48GB-RAM system is a bit faster on the rare
>>>> occasions when it can fully profit from the large RAM (large time lapse
>>>> or stitching tasks). But even then the fast swapping onto the SDDs on
>>>>
>> the
>>
>>>> Optiplex keeps them almost at the same level of performance.
>>>> Only recently we ran into some minor problems with our ATI graphics
>>>>
>> cards
>>
>>>> which could have been prevented by using NVIDIA cards, thus I would
>>>> recommend the latter. There is definitely no need to go for Quadra
>>>>
>> cards,
>>
>>>> they are super expensive and receive less updates and patches than the
>>>> gaming cards.
>>>> I hope this helps you in your decision for your new systems.
>>>> Best,
>>>> Oliver
>>>>
>>>>
>>>> ----------------------------------------------------------------
>>>> Oliver Biehlmaier, PhD
>>>> Head of Imaging Core Facility
>>>> Biozentrum, University of Basel
>>>> Klingelbergstrasse 50/70
>>>> 4056 Basel
>>>> Switzerland
>>>>
>>>> Tel: +41 (61) 267 20 73
>>>> Email: [log in to unmask]<mailto:
>>>>
>> [log in to unmask]>
>>
>>>> http://www.biozentrum.unibas.ch/imcf
>>>> ----------------------------------------------------------------
>>>>
>>>> _________________
>>>> From: Arvydas Matiukas<[log in to unmask]<mailto:
>>>>
>> [log in to unmask]>>
>>
>>>> To:=20
>>>> [log in to unmask]<mailto:
>>>>
>> [log in to unmask]>=
>>
>>> =3D
>>>
>>>> 20
>>>> Sent: Friday, March 8, 2013 12:24 PM
>>>> Subject: Computer for image analysis
>>>>
>>>> *****
>>>> To join, leave or search the confocal microscopy listserv, go to:
>>>> http://lists.umn.edu/cgi-bin/wa?A0=3D3Dconfocalmicroscopy
>>>> *****
>>>>
>>>> Dear listers/microscopists,
>>>>
>>>> I assume there is good time to update new trends in
>>>> image analysis hardware. The last discussions on image
>>>> analysis computer were in 2006-8. Though the basic
>>>> principles of CPU, RAM, hard drive, video card, monitor
>>>> selection still hold some new types of hardware became
>>>> popular/available, e.g. SSD drives, APU, water cooling.
>>>> Now a decent gaming computer (~$1k) has the processing power
>>>> of a 2006 expensive workstation (~$20K). I was suprised that
>>>> I was able to completely overhaul my 8 year old ATX case
>>>> to a quad core 2GHz APU, 8GB 1600MHz RAM, 160GB SATA-2
>>>> SSD, water cooling, USB3 and SATA3 Gigabyte motherboard,
>>>> and 4 monitor 1GB video card.
>>>> for under $300 (online, after rebates).
>>>>
>>>> Now I am wiling to upgrade/overhaul my work computer which
>>>> is used to run ImageJ, Fiji, Deconvolution (Autoquant, Huygens),
>>>> Matlab, PV-Vawe, Labview, Origin. Please advice/share you thoughts
>>>> what best configuration is possible to buy for $2-3k (monitor
>>>> excluded).
>>>> My first choice would be to go with a fast gaming computer, e.g.
>>>> Dell-Alienware Aurora=3D20
>>>> Windows* 7 Ultimate, 64Bit, English
>>>> 2nd Generation Intel* Core* i7-3820 (10M Cache, Overclocked up to 4.1
>>>> GHz)
>>>> 16GB (4 X 4GB) Quad Channel DDR3 at 1600MHz
>>>> NVIDIA* GeForce* GTX 660 1.5GB GDDR5
>>>> 1TB RAID 0 (2x 500GB SATA 6Gb/s) Solid State Hybrid
>>>> 19-in-1 Media Card Reader
>>>> No Monitor
>>>> Integrated 7.1 Channel Audio
>>>>
>>>> The second choice would be to buy all components online and
>>>> build a computer myself (I have done this about 50 times over
>>>> 25 years). This option typically saves money or buys better
>>>> components,
>>>> and provides you full specs of the hardware. The con of this
>>>> approach is that it wastes some of your time to debug/make all
>>>> the hardware work together and with your software. However,
>>>> as the computer is for me not just a box but a tool I am ready
>>>> to make this sacrifice.
>>>>
>>>> BTW, is there any solid preference towards CPU Type (Intel ix/AMD/Intel
>>>> Xeon)
>>>>
>>>> Thanks for your input/advice/thoughts,
>>>> Arvydas
>>>> --------------------
>>>>
>>>>
>>> ------------------------------
>>>
>>> End of CONFOCALMICROSCOPY Digest - 8 Mar 2013 to 9 Mar 2013 (#2013-58)
>>> **********************************************************************
>>>
>>
>
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