Ratiometric FRET on Fluoview
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Vitaly Boyko |
Re: Computer for image analysis ... SSD PCI-e cards, great, die catastrophically, may have have trouble finding an optimized O.S. driver
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To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** On Dell T3500 with BIOS A04 or A13, OCZ RevoDrive 3 X2 alike will boot. requires fresh windows install. However, I would recommend LSI MegaRAID 9240-4i (-8i), Dell PERC H310 or better on DELL T3600/T3500 workstations (HP Z420/620/820) and 2-3 SSDs in RAID 0 - for data processing only. For OS and programs the newest WD 1TB Velociraptor would be OK. Streaming to RAM is a good possibility, if you have that capability and sufficient RAM. I would prefer 2-3 SSDs in RAID 0 for transient data processing (I am not sure about OCZs, I have a couple of them, the old SATA II ones, OK so far). I would give preference to Plextor M5P (We have Plextor 512GB M3P) or Samsung 840 Pro (Pro as it is MLC, do not get TLCs 840 series). Use a separate 256 or 512 GB SSD for data caching only (OCZs would be OK for data caching). If you need more details, please let me know. Vitaly ________________________________ From: Arvydas Matiukas <[hidden email]> To: [hidden email] Sent: Monday, March 11, 2013 7:11 AM Subject: Re: Computer for image analysis ... SSD PCI-e cards, great, die catastrophically, may have have trouble finding an optimized O.S. driver ***** To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** I may corroborate regarding recording time series to SSD drive. For optical electrophysiology application we needed 500 frames/sec at 128x128, 16bit resolution and repeatedly for 10-200 sec duration, Only recording to a SSD (or alternatively to RAM which would be more expensive and still require later copying to a permanent storage) could sustain the required data transfer rate. Switching back to PCIe SSD cards: does anybody was able to install OS and boot system from them . Booting should be ultra fast at 1000MB/sec data transfer, Arvydas >>> Craig Brideau 03/10/13 11:54 PM >>> ***** To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** In our microscope computers we use SSD's only for immediate experiments. The key advantage is that if you are taking volumes over a time series the drive can save each volume very quickly, allowing your time points to be closer together since you don't have to wait for a disk write to complete. Since SSD's are still fairly expensive I only put enough space in the machine for a few experiments; the users are required to move their data over the network to a central storage server rather than leaving it on the host computer. This lets us get away with smaller and cheaper SSD's (or small but good quality SSDs for reasonable prices) while still having secure storage after the fact. I agree with George that you shouldn't leave anything on them long term. That said, some high-end servers use banks of SSD's rather than hard disks when the data has to be accessed frequently. They get around the potential reliability issue by using RAID arrays of SSD's. This is pricey, but very efficient for critical applications. Craig On Sun, Mar 10, 2013 at 2:58 PM, George McNamara wrote: > ***** > To join, leave or search the confocal microscopy listserv, go to: > http://lists.umn.edu/cgi-bin/**wa?A0=confocalmicroscopy > ***** > > 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< >> [hidden email]> 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" >>>> 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> >>>> 412-352-2277 >>>> >>>> >>>> >>>> >>>> >>>> >>>> On 3/9/13 3:39 AM, "Oliver Biehlmaier" >>>> > >>>> >>>> >>> 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: [hidden email]<**mailto: >>>>> >>>>> >>>> [hidden email]> >>> >>> >>>> http://www.biozentrum.unibas.**ch/imcf >>>>> ------------------------------**------------------------------**---- >>>>> >>>>> _________________ >>>>> From: Arvydas Matiukas>>>> >>>>> >>>> [hidden email]>> >>> >>> >>>> To:=20 >>>>> [hidden email].**EDU >>>>> >>>> >>>>> >>>> [hidden email].**EDU >= >>> >>> >>>> =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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Craig Brideau |
Re: Computer for image analysis ... SSD PCI-e cards, great, die catastrophically, may have have trouble finding an optimized O.S. driver
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In reply to this post by Watkins, Simon C
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To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** You CAN boot from a PCI-e SSD if it comes with drivers and if your OS install supports loading drivers at install time. Windows 7 seems to be able to do this, and I even managed it with XP, although I had to dig up an old floppy drive (of all things) to pull it off. Many of these PCI-e SSD's are actually RAID 0 arrays (data striping for faster access) so you need the RAID drivers handy at install time. Craig On Mon, Mar 11, 2013 at 5:41 AM, Watkins, Simon C <[hidden email]> wrote: > ***** > To join, leave or search the confocal microscopy listserv, go to: > http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy > ***** > > I think we will all be using SSD arrays in the near future. The CMOS > cameras from all companies generate about 1.8 gigabytes of data/second > when maxed, you have no choice but to use SSD arrays, we put raid 0 Sata 3 > arrays of CMOS drives in all our high speed systems. Normally half a > terabyte suffices, we use 120 gig OCZ drives ($110 ea from amazon) a > Startech 4 drive backplane ($92) and a HighPoint RocketRAID 640 4 SATA > Port PCI-Express 2.0 x4 SATA 6Gb/s RAID Controller ($102). Basically the > whole thing costs about $650, fills a spare Cdrom slot and solves all the > problemsŠfor us (it does solve our CMOS buffering problem). > S > > 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 3/11/13 7:11 AM, "Arvydas Matiukas" <[hidden email]> wrote: > > >***** > >To join, leave or search the confocal microscopy listserv, go to: > >http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy > >***** > > > >I may corroborate regarding recording time series to SSD drive. > >For optical electrophysiology application we needed 500 frames/sec > >at 128x128, 16bit resolution and repeatedly for 10-200 sec duration, > >Only recording to a SSD (or alternatively to RAM which would be > >more expensive and still require later copying to a permanent storage) > >could sustain the required data transfer rate. > > > >Switching back to PCIe SSD cards: does anybody was able to install OS > >and boot > >system from them . Booting should be ultra fast at 1000MB/sec data > >transfer, > > > >Arvydas > > > > > >>>> Craig Brideau 03/10/13 11:54 PM >>> > >***** > >To join, leave or search the confocal microscopy listserv, go to: > >http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy > >***** > > > >In our microscope computers we use SSD's only for immediate experiments. > > The key advantage is that if you are taking volumes over a time series > >the > >drive can save each volume very quickly, allowing your time points to be > >closer together since you don't have to wait for a disk write to complete. > > Since SSD's are still fairly expensive I only put enough space in the > >machine for a few experiments; the users are required to move their data > >over the network to a central storage server rather than leaving it on the > >host computer. This lets us get away with smaller and cheaper SSD's (or > >small but good quality SSDs for reasonable prices) while still having > >secure storage after the fact. I agree with George that you shouldn't > >leave anything on them long term. That said, some high-end servers use > >banks of SSD's rather than hard disks when the data has to be accessed > >frequently. They get around the potential reliability issue by using RAID > >arrays of SSD's. This is pricey, but very efficient for critical > >applications. > > > >Craig > > > > > >On Sun, Mar 10, 2013 at 2:58 PM, George McNamara > >wrote: > > > >> ***** > >> To join, leave or search the confocal microscopy listserv, go to: > >> http://lists.umn.edu/cgi-bin/**wa?A0=confocalmicroscopy > >> ***** > >> > >> 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< > >>> [hidden email]> 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" > >>>>> 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> > >>>>> 412-352-2277 > >>>>> > >>>>> > >>>>> > >>>>> > >>>>> > >>>>> > >>>>> On 3/9/13 3:39 AM, "Oliver Biehlmaier" > >>>>> > > >>>>> > >>>>> > >>>> 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: [hidden email]<**mailto: > >>>>>> > >>>>>> > >>>>> [hidden email]> > >>>> > >>>> > >>>>> http://www.biozentrum.unibas.**ch/imcf > >>>>>> ------------------------------**------------------------------**---- > >>>>>> > >>>>>> _________________ > >>>>>> From: Arvydas Matiukas>>>> > >>>>>> > >>>>> [hidden email]>> > >>>> > >>>> > >>>>> To:=20 > >>>>>> [hidden email].**EDU > >>>>>> >>>> > >>>>>> > >>>>> [hidden email].**EDU >= > >>>> > >>>> > >>>>> =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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Chris Tully |
Re: Computer for image analysis ... SSD PCI-e cards, great, die catastrophically, may have have trouble finding an optimized O.S. driver
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In reply to this post by Craig Brideau
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To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** I have to agree with all of the comments on the volatility of SSD drives. I've seen some gaming sites suggest using them for your OS to get the absolute fastest performance, but I would personally shy away from any long term storage on an SSD. Instead use it as a short term parking place. A well designed time lapse system should allow you to direct the live acquisitions to an SSD and then use the idle periods between acquisitions to move data to slower more permanent HD storage. Depending on your needs, you can also improve the performance of high quality HDs by using a striping RAID configuration. For example, using four disks in a RAID 5 configuration you should be able to write a file in slightly more than 1/3 the time it would take to write that same file to a single disk. Still no where near as fast as an SSD but respectable none the less. Chris Tully Microscopy and Image Analysis Expert [hidden email] 240-475-9753 (c) [image: View my profile on LinkedIn]<http://www.linkedin.com/in/christully/> On Mon, Mar 11, 2013 at 12:54 AM, Craig Brideau <[hidden email]>wrote: > ***** > To join, leave or search the confocal microscopy listserv, go to: > http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy > ***** > > In our microscope computers we use SSD's only for immediate experiments. > The key advantage is that if you are taking volumes over a time series the > drive can save each volume very quickly, allowing your time points to be > closer together since you don't have to wait for a disk write to complete. > Since SSD's are still fairly expensive I only put enough space in the > machine for a few experiments; the users are required to move their data > over the network to a central storage server rather than leaving it on the > host computer. This lets us get away with smaller and cheaper SSD's (or > small but good quality SSDs for reasonable prices) while still having > secure storage after the fact. I agree with George that you shouldn't > leave anything on them long term. That said, some high-end servers use > banks of SSD's rather than hard disks when the data has to be accessed > frequently. They get around the potential reliability issue by using RAID > arrays of SSD's. This is pricey, but very efficient for critical > applications. > > Craig > > > On Sun, Mar 10, 2013 at 2:58 PM, George McNamara > <[hidden email]>wrote: > > > ***** > > To join, leave or search the confocal microscopy listserv, go to: > > http://lists.umn.edu/cgi-bin/**wa?A0=confocalmicroscopy< > http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy> > > ***** > > > > 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< > 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< > 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< > >> [hidden email]> wrote: > >> > >> > >> > >>> ***** > >>> To join, leave or search the confocal microscopy listserv, go to: > >>> http://lists.umn.edu/cgi-bin/**wa?A0=confocalmicroscopy< > 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"<[hidden email]> > >>>> 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< > 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/ <http://Www.cbi.pitt.edu/ > >> > >>>> 412-352-2277 > >>>> > >>>> > >>>> > >>>> > >>>> > >>>> > >>>> On 3/9/13 3:39 AM, "Oliver Biehlmaier"<oliver.biehlmaier@**UNIBAS.CH< > [hidden email]> > >>>> > > >>>> > >>>> > >>> 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: [hidden email]<**mailto: > >>>>> > >>>>> > >>>> [hidden email]> > >>> > >>> > >>>> http://www.biozentrum.unibas.**ch/imcf< > http://www.biozentrum.unibas.ch/imcf> > >>>>> ------------------------------**------------------------------**---- > >>>>> > >>>>> _________________ > >>>>> From: Arvydas Matiukas<[hidden email]<**mailto: > >>>>> > >>>>> > >>>> [hidden email]>> > >>> > >>> > >>>> To:=20 > >>>>> [hidden email].**EDU <[hidden email] > > > >>>>> <mailto: > >>>>> > >>>>> > >>>> [hidden email].**EDU <[hidden email] > >>= > >>> > >>> > >>>> =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< > 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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Cameron Nowell-2 |
Re: Computer for image analysis
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In reply to this post by Arvydas Matiukas
*****
To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** Hi All, I thought I might chip in one of our recent experiences. Firstly all the discussions going on re components I fully agree with. One thing that has been mentioned is gaming cards. For sure go for the best gaming card you can lay your hands on (even the most expensive are not that much for a total beast of a card). The issue with buying pre-configured workstations is that they will all come with a Nvidia Quadro or AMD FireGL card. These are workstation glass cards that come with (supposably) better support and refined drivers. They also carry a price premium of 2-3x on top of the equivalent gaming card. So if you can build your own system or buy a preconfigured workstation with the lowest end card you can and upgrade it yourself. Just make sure the power supply can take it. Now one thing from our recent experience is file formats. We have a user who collects huge, and I mean really huge, data sets. These are between 50 and 120GB for each file. Large area tile scans, 4-5 channels and 200+ z slices. Yeah scary. Now if these are captured on a leica system there doesn't seem to be any problem dealing with them (opening, stitching, manipulating etc). but when they are capture on a zeiss system the LSM file format seems to bring things to a grinding halt. There doesn't seem to be the capability to open parts of the image as needed, the whole thing has to get loaded into ram (and if there isn't enough ram it then gets paged). Interestingly if you convert it all to say an imaris ims file, it uses vaery minimal resources and can be easily manipulated. So even if you have a true beast of a machine, different file formats may bring it to its knees anyway. Cheers Cam Cameron J. Nowell Centre for Dynamic Imaging The Walter and Eliza Hall Institute of Medical Research 1G Royal Parade Parkville, Victoria 3052 Australia Phone: +61 3 9345 2871 Mobile: +61422882700 Fax: +61 3 9347 0852 Facility Website LinkedIn Profile -----Original Message----- From: Confocal Microscopy List [mailto:[hidden email]] On Behalf Of Arvydas Matiukas Sent: Saturday, 9 March 2013 4:24 AM To: [hidden email] Subject: Computer for image analysis ***** To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** 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 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 -------------------- Arvydas Matiukas, Ph.D. Director of Confocal&Two-Photon Core Department of Neurosci& Physiology SUNY Upstate Medical University 766 Irving Ave., WH 3167 Syracuse, NY 13210 tel.: 315-464-7997 fax: 315-464-8014 email: [hidden email] >>> Tim Feinstein <[hidden email]> 3/7/2013 5:13 PM >>> ***** To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** Hi Chris, Agreed about FRET with a dichroic-based beam splitter on the emission side such as a DualView or QuadView. No commercial interest, but our group uses a DV2 widefield/TIRF system for quantitative FRET just about all day every day. As the executives say, drive for show and putt for dough. In general I'd always go widefield if quantitative is more important than spatial. JP, unless I remember wrong the 510 has its detectors in a series with switchable dichroic filters between each detector (for example, a 515-ish nm longpass dichroic between detectors 1 and 2 if you want to see cerulean/venus/FRET). Thus it collects each emission channel simultaneously and can go as fast as it can scan a line and alternate lasers, which pass through a two-notch excitation filter. Creulean-FRET bleed-through is still a bear of course, but it always is, and there are long established ways to correct that. cheers, TF Timothy Feinstein, PhD Visiting Research Associate Laboratory for GPCR Biology Dept. of Pharmacology & Chemical Biology University of Pittsburgh, School of Medicine BST W1301, 200 Lothrop St. Pittsburgh, PA 15261 On Mar 7, 2013, at 4:23 PM, Chris Tully wrote: > ***** > To join, leave or search the confocal microscopy listserv, go to: > http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy > ***** > > If speed is the issue and you can illuminate with broad spectrum light, you > might want to consider the QV2 from Photometrics: > http://www.photometrics.com/products/multichannel/ > > It allows a single camera to simultaneously image up to 4 channels by > splitting the chip into quadrants and splitting the light into four paths > that each pass through a different emission filter before hitting the CCD. > > Just clarify, I have never personally used one of these in a research > project, but I have worked with one in developing software support for the > resulting images. I do not work for Photometrics. > > Chris Tully > Microscopy and Image Analysis Expert > [hidden email] > 240-475-9753 (c) > > [image: View my profile on LinkedIn]<http://www.linkedin.com/in/christully/> > > > On Tue, Mar 5, 2013 at 2:09 PM, Jean-Pierre CLAMME < > [hidden email]> wrote: > >> ***** >> To join, leave or search the confocal microscopy listserv, go to: >> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >> ***** >> >> Hi Andreas, >> >> The issue is not grouping channels in the sequential box and >> and frame. The issue is changing filter sets quickly. To take the 3 images >> DD, DA, AA the filter/light pathway has to be changed between images. DD >> and DA or DD and AA can be taken in the same configuration, but AA and DA >> can't. So the only way I can see is to use the Virtual channels and that >> is too slow line by Line. >> >> Best >> >> JP >> >> >> >> >> >> Confocal Microscopy List <[hidden email]> wrote >> 03/05/2013 07:01:06 AM: >> >>> Andreas Bruckbauer <[hidden email]> Sent by: Confocal Microscopy >>> List <[hidden email]> >>> >>> 03/05/2013 07:05 AM >>> >>> Please respond to >>> Confocal Microscopy List <[hidden email]> >>> >>> To >>> >>> [hidden email] >>> >>> cc >>> >>> Subject >>> >>> Re: Ratiometric FRET on Fluoview >>> >>> ***** >>> To join, leave or search the confocal microscopy listserv, go to: >>> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >>> ***** >> >>> I have not used it for FRET, but we have a sequential tick box at >>> the bottom of the window with the channel parameters. When ticked >>> can select "frame by frame" or "line by line" aquisition and how the >>> channels will be grouped together. >> >>> best wishes >> >>> Andreas >> >>> >>> -----Original Message----- >>> From: Jean-Pierre CLAMME <[hidden email]> >>> To: CONFOCALMICROSCOPY <[hidden email]> >>> Sent: Mon, 4 Mar 2013 22:44 >>> Subject: Ratiometric FRET on Fluoview >> >>> >>> ***** >>> To join, leave or search the confocal microscopy listserv, go to: >>> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >>> ***** >> >>> Hello, >> >>> I saw a paper about Ratiometric FRET (Roszik, Cytometer 2009) >>> line by line acquisition of the 3 images (IDA, IDD, IAA). The authors >>> mentioned the use of a LSM 510. >> >>> I don't know the LSM510, but I have a fluoview 1000 and the only way I >> can >>> see how to do that is using the "virual Channels" . However that would >> be >>> image by image and not line by line. >> >>> Does anyone has done ratiometric FRET on the fluoview and what method >> did >>> you use ? >> >>> Thank you and Best regards, >> >>> JP >> >>> >>> - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - >>> Jean-Pierre CLAMME, PhD >>> Chief Scientist >>> Nitto Denko Technical >>> 501 Via Del Monte >>> Oceanside, CA 92058 >>> E-mail: [hidden email] >>> Phone: 1-760-696-9428 >> ______________________________________________________________________ The information in this email is confidential and intended solely for the addressee. You must not disclose, forward, print or use it without the permission of the sender. ______________________________________________________________________ |
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Arvydas Matiukas |
Re: Computer for image analysis...OS choice
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*****
To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** Dear listers/image analysts, Our discussion so far mostly concerned hardware and to some extent image analysis software. Just few mentioning of Mac vs PC. I am a PC person which still gives few OS choices: Windows (7 Pro x64, 7 Ultimate x64), Linux (Ubuntu?), ...BSD? I wonder how the choice of OS may affect image analysis software performance and manipulation of extra large files (>10GB see Cameron posting below). Best, Arvydas >>> Cameron Nowell <[hidden email]> 3/11/2013 4:31 PM >>> ***** To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** Hi All, I thought I might chip in one of our recent experiences. Firstly all the discussions going on re components I fully agree with. One thing that has been mentioned is gaming cards. For sure go for the best gaming card you can lay your hands on (even the most expensive are not that much for a total beast of a card). The issue with buying pre-configured workstations is that they will all come with a Nvidia Quadro or AMD FireGL card. These are workstation glass cards that come with (supposably) better support and refined drivers. They also carry a price premium of 2-3x on top of the equivalent gaming card. So if you can build your own system or buy a preconfigured workstation with the lowest end card you can and upgrade it yourself. Just make sure the power supply can take it. Now one thing from our recent experience is file formats. We have a user who collects huge, and I mean really huge, data sets. These are between 50 and 120GB for each file. Large area tile scans, 4-5 channels and 200+ z slices. Yeah scary. Now if these are captured on a leica system there doesn't seem to be any problem dealing with them (opening, stitching, manipulating etc). but when they are capture on a zeiss system the LSM file format seems to bring things to a grinding halt. There doesn't seem to be the capability to open parts of the image as needed, the whole thing has to get loaded into ram (and if there isn't enough ram it then gets paged). Interestingly if you convert it all to say an imaris ims file, it uses vaery minimal resources and can be easily manipulated. So even if you have a true beast of a machine, different file formats may bring it to its knees anyway. Cheers Cam Cameron J. Nowell Centre for Dynamic Imaging The Walter and Eliza Hall Institute of Medical Research 1G Royal Parade Parkville, Victoria 3052 Australia Phone: +61 3 9345 2871 Mobile: +61422882700 Fax: +61 3 9347 0852 Facility Website LinkedIn Profile -----Original Message----- From: Confocal Microscopy List [mailto:[hidden email]] On Behalf Of Arvydas Matiukas Sent: Saturday, 9 March 2013 4:24 AM To: [hidden email] Subject: Computer for image analysis ***** To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** 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 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 -------------------- Arvydas Matiukas, Ph.D. Director of Confocal&Two-Photon Core Department of Neurosci& Physiology SUNY Upstate Medical University 766 Irving Ave., WH 3167 Syracuse, NY 13210 tel.: 315-464-7997 fax: 315-464-8014 email: [hidden email] >>> Tim Feinstein <[hidden email]> 3/7/2013 5:13 PM >>> ***** To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** Hi Chris, Agreed about FRET with a dichroic-based beam splitter on the emission side such as a DualView or QuadView. No commercial interest, but our group uses a DV2 widefield/TIRF system for quantitative FRET just about all day every day. As the executives say, drive for show and putt for dough. In general I'd always go widefield if quantitative is more important than spatial. JP, unless I remember wrong the 510 has its detectors in a series with switchable dichroic filters between each detector (for example, a 515-ish nm longpass dichroic between detectors 1 and 2 if you want to see cerulean/venus/FRET). Thus it collects each emission channel simultaneously and can go as fast as it can scan a line and alternate lasers, which pass through a two-notch excitation filter. Creulean-FRET bleed-through is still a bear of course, but it always is, and there are long established ways to correct that. cheers, TF Timothy Feinstein, PhD Visiting Research Associate Laboratory for GPCR Biology Dept. of Pharmacology & Chemical Biology University of Pittsburgh, School of Medicine BST W1301, 200 Lothrop St. Pittsburgh, PA 15261 On Mar 7, 2013, at 4:23 PM, Chris Tully wrote: > ***** > To join, leave or search the confocal microscopy listserv, go to: > http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy > ***** > > If speed is the issue and you can illuminate with broad spectrum light, you > might want to consider the QV2 from Photometrics: > http://www.photometrics.com/products/multichannel/ > > It allows a single camera to simultaneously image up to 4 channels by > splitting the chip into quadrants and splitting the light into four paths > that each pass through a different emission filter before hitting the CCD. > > Just clarify, I have never personally used one of these in a research > project, but I have worked with one in developing software support for the > resulting images. I do not work for Photometrics. > > Chris Tully > Microscopy and Image Analysis Expert > [hidden email] > 240-475-9753 (c) > > [image: View my profile on LinkedIn]<http://www.linkedin.com/in/christully/> > > > On Tue, Mar 5, 2013 at 2:09 PM, Jean-Pierre CLAMME < > [hidden email]> wrote: > >> ***** >> To join, leave or search the confocal microscopy listserv, go to: >> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >> ***** >> >> Hi Andreas, >> >> The issue is not grouping channels in the sequential box and >> and frame. The issue is changing filter sets quickly. To take the 3 images >> DD, DA, AA the filter/light pathway has to be changed between images. DD >> and DA or DD and AA can be taken in the same configuration, but AA and DA >> can't. So the only way I can see is to use the Virtual channels and that >> is too slow line by Line. >> >> Best >> >> JP >> >> >> >> >> >> Confocal Microscopy List <[hidden email]> wrote >> 03/05/2013 07:01:06 AM: >> >>> Andreas Bruckbauer <[hidden email]> Sent by: Confocal Microscopy >>> List <[hidden email]> >>> >>> 03/05/2013 07:05 AM >>> >>> Please respond to >>> Confocal Microscopy List <[hidden email]> >>> >>> To >>> >>> [hidden email] >>> >>> cc >>> >>> Subject >>> >>> Re: Ratiometric FRET on Fluoview >>> >>> ***** >>> To join, leave or search the confocal microscopy listserv, go to: >>> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >>> ***** >> >>> I have not used it for FRET, but we have a sequential tick box at >>> the bottom of the window with the channel parameters. When ticked >>> can select "frame by frame" or "line by line" aquisition and how the >>> channels will be grouped together. >> >>> best wishes >> >>> Andreas >> >>> >>> -----Original Message----- >>> From: Jean-Pierre CLAMME <[hidden email]> >>> To: CONFOCALMICROSCOPY <[hidden email]> >>> Sent: Mon, 4 Mar 2013 22:44 >>> Subject: Ratiometric FRET on Fluoview >> >>> >>> ***** >>> To join, leave or search the confocal microscopy listserv, go to: >>> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >>> ***** >> >>> Hello, >> >>> I saw a paper about Ratiometric FRET (Roszik, Cytometer 2009) >>> line by line acquisition of the 3 images (IDA, IDD, IAA). The authors >>> mentioned the use of a LSM 510. >> >>> I don't know the LSM510, but I have a fluoview 1000 and the only way I >> can >>> see how to do that is using the "virual Channels" . However that would >> be >>> image by image and not line by line. >> >>> Does anyone has done ratiometric FRET on the fluoview and what method >> did >>> you use ? >> >>> Thank you and Best regards, >> >>> JP >> >>> >>> - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - >>> Jean-Pierre CLAMME, PhD >>> Chief Scientist >>> Nitto Denko Technical >>> 501 Via Del Monte >>> Oceanside, CA 92058 >>> E-mail: [hidden email] >>> Phone: 1-760-696-9428 >> ______________________________________________________________________ The information in this email is confidential and intended solely for the addressee. You must not disclose, forward, print or use it without the permission of the sender. ______________________________________________________________________ |
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Scott, Mark |
Re: Computer for image analysis...OS choice
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To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** Dear Arvydas, Obviously a lot will depend on the software packages you plan to run, but in my experience Linux seems to cope better with heavy processing tasks on large data sets than Windows traditionally does, i'm sure someone with more knowledge of the inner workings of this may be able to shed light on it but it seems to me that Ubuntu (and Suse which i've used in the past) utilise multiple cores a lot better than Windows but perhaps i'm just stretching. The best thing to do would be to dual boot a PC and have both Windows AND Ubuntu running and test them out for your needs. I would be very keen to hear how the results go since i'm only running Ubuntu under VMWare rather than dual booting it. Thanks Mark -----Original Message----- From: Confocal Microscopy List [mailto:[hidden email]] On Behalf Of Arvydas Matiukas Sent: 12 March 2013 17:53 To: [hidden email] Subject: Re: Computer for image analysis...OS choice ***** To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** Dear listers/image analysts, Our discussion so far mostly concerned hardware and to some extent image analysis software. Just few mentioning of Mac vs PC. I am a PC person which still gives few OS choices: Windows (7 Pro x64, 7 Ultimate x64), Linux (Ubuntu?), ...BSD? I wonder how the choice of OS may affect image analysis software performance and manipulation of extra large files (>10GB see Cameron posting below). Best, Arvydas >>> Cameron Nowell <[hidden email]> 3/11/2013 4:31 PM >>> ***** To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** Hi All, I thought I might chip in one of our recent experiences. Firstly all the discussions going on re components I fully agree with. One thing that has been mentioned is gaming cards. For sure go for the best gaming card you can lay your hands on (even the most expensive are not that much for a total beast of a card). The issue with buying pre-configured workstations is that they will all come with a Nvidia Quadro or AMD FireGL card. These are workstation glass cards that come with (supposably) better support and refined drivers. They also carry a price premium of 2-3x on top of the equivalent gaming card. So if you can build your own system or buy a preconfigured workstation with the lowest end card you can and upgrade it yourself. Just make sure the power supply can take it. Now one thing from our recent experience is file formats. We have a user who collects huge, and I mean really huge, data sets. These are between 50 and 120GB for each file. Large area tile scans, 4-5 channels and 200+ z slices. Yeah scary. Now if these are captured on a leica system there doesn't seem to be any problem dealing with them (opening, stitching, manipulating etc). but when they are capture on a zeiss system the LSM file format seems to bring things to a grinding halt. There doesn't seem to be the capability to open parts of the image as needed, the whole thing has to get loaded into ram (and if there isn't enough ram it then gets paged). Interestingly if you convert it all to say an imaris ims file, it uses vaery minimal resources and can be easily manipulated. So even if you have a true beast of a machine, different file formats may bring it to its knees anyway. Cheers Cam Cameron J. Nowell Centre for Dynamic Imaging The Walter and Eliza Hall Institute of Medical Research 1G Royal Parade Parkville, Victoria 3052 Australia Phone: +61 3 9345 2871 Mobile: +61422882700 Fax: +61 3 9347 0852 Facility Website LinkedIn Profile -----Original Message----- From: Confocal Microscopy List [mailto:[hidden email]] On Behalf Of Arvydas Matiukas Sent: Saturday, 9 March 2013 4:24 AM To: [hidden email] Subject: Computer for image analysis ***** To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** 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 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 -------------------- Arvydas Matiukas, Ph.D. Director of Confocal&Two-Photon Core Department of Neurosci& Physiology SUNY Upstate Medical University 766 Irving Ave., WH 3167 Syracuse, NY 13210 tel.: 315-464-7997 fax: 315-464-8014 email: [hidden email] >>> Tim Feinstein <[hidden email]> 3/7/2013 5:13 PM >>> ***** To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** Hi Chris, Agreed about FRET with a dichroic-based beam splitter on the emission side such as a DualView or QuadView. No commercial interest, but our group uses a DV2 widefield/TIRF system for quantitative FRET just about all day every day. As the executives say, drive for show and putt for dough. In general I'd always go widefield if quantitative is more important than spatial. JP, unless I remember wrong the 510 has its detectors in a series with switchable dichroic filters between each detector (for example, a 515-ish nm longpass dichroic between detectors 1 and 2 if you want to see cerulean/venus/FRET). Thus it collects each emission channel simultaneously and can go as fast as it can scan a line and alternate lasers, which pass through a two-notch excitation filter. Creulean-FRET bleed-through is still a bear of course, but it always is, and there are long established ways to correct that. cheers, TF Timothy Feinstein, PhD Visiting Research Associate Laboratory for GPCR Biology Dept. of Pharmacology & Chemical Biology University of Pittsburgh, School of Medicine BST W1301, 200 Lothrop St. Pittsburgh, PA 15261 On Mar 7, 2013, at 4:23 PM, Chris Tully wrote: > ***** > To join, leave or search the confocal microscopy listserv, go to: > http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy > ***** > > If speed is the issue and you can illuminate with broad spectrum light, you > might want to consider the QV2 from Photometrics: > http://www.photometrics.com/products/multichannel/ > > It allows a single camera to simultaneously image up to 4 channels by > splitting the chip into quadrants and splitting the light into four paths > that each pass through a different emission filter before hitting the CCD. > > Just clarify, I have never personally used one of these in a research > project, but I have worked with one in developing software support for the > resulting images. I do not work for Photometrics. > > Chris Tully > Microscopy and Image Analysis Expert > [hidden email] > 240-475-9753 (c) > > [image: View my profile on LinkedIn]<http://www.linkedin.com/in/christully/> > > > On Tue, Mar 5, 2013 at 2:09 PM, Jean-Pierre CLAMME < > [hidden email]> wrote: > >> ***** >> To join, leave or search the confocal microscopy listserv, go to: >> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >> ***** >> >> Hi Andreas, >> >> The issue is not grouping channels in the sequential box and >> and frame. The issue is changing filter sets quickly. To take the 3 images >> DD, DA, AA the filter/light pathway has to be changed between images. DD >> and DA or DD and AA can be taken in the same configuration, but AA and DA >> can't. So the only way I can see is to use the Virtual channels and that >> is too slow line by Line. >> >> Best >> >> JP >> >> >> >> >> >> Confocal Microscopy List <[hidden email]> wrote >> 03/05/2013 07:01:06 AM: >> >>> Andreas Bruckbauer <[hidden email]> Sent by: Confocal Microscopy >>> List <[hidden email]> >>> >>> 03/05/2013 07:05 AM >>> >>> Please respond to >>> Confocal Microscopy List <[hidden email]> >>> >>> To >>> >>> [hidden email] >>> >>> cc >>> >>> Subject >>> >>> Re: Ratiometric FRET on Fluoview >>> >>> ***** >>> To join, leave or search the confocal microscopy listserv, go to: >>> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >>> ***** >> >>> I have not used it for FRET, but we have a sequential tick box at >>> the bottom of the window with the channel parameters. When ticked >>> can select "frame by frame" or "line by line" aquisition and how the >>> channels will be grouped together. >> >>> best wishes >> >>> Andreas >> >>> >>> -----Original Message----- >>> From: Jean-Pierre CLAMME <[hidden email]> >>> To: CONFOCALMICROSCOPY <[hidden email]> >>> Sent: Mon, 4 Mar 2013 22:44 >>> Subject: Ratiometric FRET on Fluoview >> >>> >>> ***** >>> To join, leave or search the confocal microscopy listserv, go to: >>> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >>> ***** >> >>> Hello, >> >>> I saw a paper about Ratiometric FRET (Roszik, Cytometer 2009) >>> line by line acquisition of the 3 images (IDA, IDD, IAA). The authors >>> mentioned the use of a LSM 510. >> >>> I don't know the LSM510, but I have a fluoview 1000 and the only way I >> can >>> see how to do that is using the "virual Channels" . However that would >> be >>> image by image and not line by line. >> >>> Does anyone has done ratiometric FRET on the fluoview and what method >> did >>> you use ? >> >>> Thank you and Best regards, >> >>> JP >> >>> >>> - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - >>> Jean-Pierre CLAMME, PhD >>> Chief Scientist >>> Nitto Denko Technical >>> 501 Via Del Monte >>> Oceanside, CA 92058 >>> E-mail: [hidden email] >>> Phone: 1-760-696-9428 >> ______________________________________________________________________ The information in this email is confidential and intended solely for the addressee. You must not disclose, forward, print or use it without the permission of the sender. ______________________________________________________________________ |
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Casey Laris-3 |
Re: Computer for image analysis...OS choice
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To join, leave or search the confocal microscopy listserv, go to: http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy ***** Another thing to think about is exactly what image processing type/image processing tool you will use. As an example, we routinely use Matlab for custom image processing for our clients. Execution speeds are a routine consideration for the larger - many gigapixel - images we get from our whole slide images. Matlab does a nice job of using both the CPU and GPU available on the system. Optimizing the CPU is probably to be expected at this point but taking advantage of the GPU can give significant improvements in processing speed. We routinely see differences in execution times in the 1X to 10X range. This is all a long winded way of saying that this only works with graphics that support Nvidia's GPU parallel computing platform called CUDA. Here are couple links (I have no commercial affiliation with either company) What is CUDA | NVIDIA Developer Zone. MATLAB GPU Computing with NVIDIA CUDA-Enabled GPUs There are myriad software set-ups of course but you should definitely think about matching your software with hardware if there are large data sets to be processed. A very similar price might end up with very different day to day processing times. Good luck and best wishes! Casey ----------------------------------------------- Casey Laris Reveal Biosciences On Mar 13, 2013, at 3:20 AM, "Scott, Mark" <[hidden email]> wrote: > ***** > To join, leave or search the confocal microscopy listserv, go to: > http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy > ***** > > Dear Arvydas, > > Obviously a lot will depend on the software packages you plan to run, but in my experience Linux seems to cope better with heavy processing tasks on large data sets than Windows traditionally does, i'm sure someone with more knowledge of the inner workings of this may be able to shed light on it but it seems to me that Ubuntu (and Suse which i've used in the past) utilise multiple cores a lot better than Windows but perhaps i'm just stretching. > > The best thing to do would be to dual boot a PC and have both Windows AND Ubuntu running and test them out for your needs. I would be very keen to hear how the results go since i'm only running Ubuntu under VMWare rather than dual booting it. > > Thanks > Mark > > > > -----Original Message----- > From: Confocal Microscopy List [mailto:[hidden email]] On Behalf Of Arvydas Matiukas > Sent: 12 March 2013 17:53 > To: [hidden email] > Subject: Re: Computer for image analysis...OS choice > > ***** > To join, leave or search the confocal microscopy listserv, go to: > http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy > ***** > > Dear listers/image analysts, > > Our discussion so far mostly concerned hardware and to some extent > image analysis software. Just few mentioning of Mac vs PC. > > I am a PC person which still gives few OS choices: Windows (7 Pro x64, > 7 Ultimate x64), Linux (Ubuntu?), ...BSD? > I wonder how the choice of OS may affect image analysis software > performance and manipulation of extra large files (>10GB see Cameron > posting below). > > Best, > Arvydas > > >>>> Cameron Nowell <[hidden email]> 3/11/2013 4:31 PM >>> > ***** > To join, leave or search the confocal microscopy listserv, go to: > http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy > ***** > > Hi All, > > I thought I might chip in one of our recent experiences. Firstly all the discussions going on re components I fully agree with. One thing that has been mentioned is gaming cards. For sure go for the best gaming card you can lay your hands on (even the most expensive are not that much for a total beast of a card). The issue with buying pre-configured workstations is that they will all come with a Nvidia Quadro or AMD FireGL card. These are workstation glass cards that come with (supposably) better support and refined drivers. They also carry a price premium of 2-3x on top of the equivalent gaming card. So if you can build your own system or buy a preconfigured workstation with the lowest end card you can and upgrade it yourself. Just make sure the power supply can take it. > > Now one thing from our recent experience is file formats. We have a user who collects huge, and I mean really huge, data sets. These are between 50 and 120GB for each file. Large area tile scans, 4-5 channels and 200+ z slices. Yeah scary. Now if these are captured on a leica system there doesn't seem to be any problem dealing with them (opening, stitching, manipulating etc). but when they are capture on a zeiss system the LSM file format seems to bring things to a grinding halt. There doesn't seem to be the capability to open parts of the image as needed, the whole thing has to get loaded into ram (and if there isn't enough ram it then gets paged). Interestingly if you convert it all to say an imaris ims file, it uses vaery minimal resources and can be easily manipulated. > > So even if you have a true beast of a machine, different file formats may bring it to its knees anyway. > > Cheers > > Cam > > > Cameron J. Nowell > Centre for Dynamic Imaging > The Walter and Eliza Hall Institute of Medical Research > 1G Royal Parade > Parkville, Victoria 3052 > Australia > > Phone: +61 3 9345 2871 > Mobile: +61422882700 > Fax: +61 3 9347 0852 > > Facility Website > LinkedIn Profile > > > > -----Original Message----- > From: Confocal Microscopy List [mailto:[hidden email]] On Behalf Of Arvydas Matiukas > Sent: Saturday, 9 March 2013 4:24 AM > To: [hidden email] > Subject: Computer for image analysis > > ***** > To join, leave or search the confocal microscopy listserv, go to: > http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy > ***** > > 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 > 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 > -------------------- > > > > > Arvydas Matiukas, Ph.D. > Director of Confocal&Two-Photon Core > Department of Neurosci& Physiology > SUNY Upstate Medical University > 766 Irving Ave., WH 3167 > Syracuse, NY 13210 > tel.: 315-464-7997 > fax: 315-464-8014 > email: [hidden email] >>>> Tim Feinstein <[hidden email]> 3/7/2013 5:13 PM >>> > ***** > To join, leave or search the confocal microscopy listserv, go to: > http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy > ***** > > Hi Chris, > > Agreed about FRET with a dichroic-based beam splitter on the emission side such as a DualView or QuadView. No commercial interest, but our group uses a DV2 widefield/TIRF system for quantitative FRET just about all day every day. As the executives say, drive for show and putt for dough. In general I'd always go widefield if quantitative is more important than spatial. > > JP, unless I remember wrong the 510 has its detectors in a series with switchable dichroic filters between each detector (for example, a 515-ish nm longpass dichroic between detectors 1 and 2 if you want to see cerulean/venus/FRET). Thus it collects each emission channel simultaneously and can go as fast as it can scan a line and alternate lasers, which pass through a two-notch excitation filter. > Creulean-FRET bleed-through is still a bear of course, but it always is, and there are long established ways to correct that. > > cheers, > > > TF > > Timothy Feinstein, PhD > Visiting Research Associate > Laboratory for GPCR Biology > Dept. of Pharmacology & Chemical Biology University of Pittsburgh, School of Medicine BST W1301, 200 Lothrop St. > Pittsburgh, PA 15261 > > On Mar 7, 2013, at 4:23 PM, Chris Tully wrote: > >> ***** >> To join, leave or search the confocal microscopy listserv, go to: >> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >> ***** >> >> If speed is the issue and you can illuminate with broad spectrum > light, you >> might want to consider the QV2 from Photometrics: >> http://www.photometrics.com/products/multichannel/ >> >> It allows a single camera to simultaneously image up to 4 channels > by >> splitting the chip into quadrants and splitting the light into four > paths >> that each pass through a different emission filter before hitting the > CCD. >> >> Just clarify, I have never personally used one of these in a > research >> project, but I have worked with one in developing software support > for the >> resulting images. I do not work for Photometrics. >> >> Chris Tully >> Microscopy and Image Analysis Expert >> [hidden email] >> 240-475-9753 (c) >> >> [image: View my profile on > LinkedIn]<http://www.linkedin.com/in/christully/> >> >> >> On Tue, Mar 5, 2013 at 2:09 PM, Jean-Pierre CLAMME < >> [hidden email]> wrote: >> >>> ***** >>> To join, leave or search the confocal microscopy listserv, go to: >>> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >>> ***** >>> >>> Hi Andreas, >>> >>> The issue is not grouping channels in the sequential box and > choosing line >>> and frame. The issue is changing filter sets quickly. To take the 3 > images >>> DD, DA, AA the filter/light pathway has to be changed between > images. DD >>> and DA or DD and AA can be taken in the same configuration, but AA > and DA >>> can't. So the only way I can see is to use the Virtual channels and > that >>> is too slow line by Line. >>> >>> Best >>> >>> JP >>> >>> >>> >>> >>> >>> Confocal Microscopy List <[hidden email]> wrote > on >>> 03/05/2013 07:01:06 AM: >>> >>>> Andreas Bruckbauer <[hidden email]> Sent by: Confocal Microscopy >>>> List > <[hidden email]> >>>> >>>> 03/05/2013 07:05 AM >>>> >>>> Please respond to >>>> Confocal Microscopy List <[hidden email]> >>>> >>>> To >>>> >>>> [hidden email] >>>> >>>> cc >>>> >>>> Subject >>>> >>>> Re: Ratiometric FRET on Fluoview >>>> >>>> ***** >>>> To join, leave or search the confocal microscopy listserv, go to: >>>> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >>>> ***** >>> >>>> I have not used it for FRET, but we have a sequential tick box at >>>> the bottom of the window with the channel parameters. When ticked > we >>>> can select "frame by frame" or "line by line" aquisition and how > the >>>> channels will be grouped together. >>> >>>> best wishes >>> >>>> Andreas >>> >>>> >>>> -----Original Message----- >>>> From: Jean-Pierre CLAMME <[hidden email]> >>>> To: CONFOCALMICROSCOPY <[hidden email]> >>>> Sent: Mon, 4 Mar 2013 22:44 >>>> Subject: Ratiometric FRET on Fluoview >>> >>>> >>>> ***** >>>> To join, leave or search the confocal microscopy listserv, go to: >>>> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy >>>> ***** >>> >>>> Hello, >>> >>>> I saw a paper about Ratiometric FRET (Roszik, Cytometer 2009) > mentioning >>>> line by line acquisition of the 3 images (IDA, IDD, IAA). The > authors >>>> mentioned the use of a LSM 510. >>> >>>> I don't know the LSM510, but I have a fluoview 1000 and the only > way I >>> can >>>> see how to do that is using the "virual Channels" . However that > would >>> be >>>> image by image and not line by line. >>> >>>> Does anyone has done ratiometric FRET on the fluoview and what > method >>> did >>>> you use ? >>> >>>> Thank you and Best regards, >>> >>>> JP >>> >>>> >>>> - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > - >>>> Jean-Pierre CLAMME, PhD >>>> Chief Scientist >>>> Nitto Denko Technical >>>> 501 Via Del Monte >>>> Oceanside, CA 92058 >>>> E-mail: [hidden email] >>>> Phone: 1-760-696-9428 >>> > > ______________________________________________________________________ > The information in this email is confidential and intended solely for the addressee. > You must not disclose, forward, print or use it without the permission of the sender. > ______________________________________________________________________ |
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