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Ratiometric FRET on Fluoview

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Jean-Pierre CLAMME-2

Ratiometric FRET on Fluoview

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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

Jean-Pierre CLAMME-2

Re: Ratiometric FRET on Fluoview sorry

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http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
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Sorry I meant

"Has anyone done ratiometric FRET on the fluoview and what method did
you use ? "

Confocal Microscopy List <[hidden email]> wrote on
03/04/2013 02:43:44 PM:

> jeanpierre clamme/NITTO@NITTO
> Sent by: Confocal Microscopy List <[hidden email]>
>
> 03/04/2013 02:45 PM
>
> Please respond to
> Confocal Microscopy List <[hidden email]>
>
> To
>
> [hidden email]
>
> cc
>
> 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

Andreas Bruckbauer

Re: Ratiometric FRET on Fluoview

In reply to this post by Jean-Pierre CLAMME-2

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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

Jean-Pierre CLAMME-2

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
*****

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

Andreas Bruckbauer

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
*****

Switching filters will always be too slow in line by line aquisition, so i think you should only switch lasers. The protocol for CFP/YFP would be to aquire with 458 excitation the CFP emission at 475 - 525 nm and the YFP emission > 525 nm and the switch to 514.5 excitation and collect only the YFP emission at > 525 nm.

best wishes

Andreas

-----Original Message-----
From: Jean-Pierre CLAMME <[hidden email]>
To: CONFOCALMICROSCOPY <[hidden email]>
Sent: Tue, 5 Mar 2013 19:09
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
*****

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:

Chris Tully

Re: Ratiometric FRET on Fluoview

In reply to this post by Jean-Pierre CLAMME-2

*****
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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
>

Tim Feinstein-2

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
*****

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
>>

Arvydas Matiukas

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
>>

Chris Tully

Re: Computer for image analysis

*****
To join, leave or search the confocal microscopy listserv, go to:
http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
*****

Arvydas,

I have always felt and still feel that when buying a new computer the most
important question is how much can you afford to spend? Once you answer
that question, the next is what will get you the most bang for the buck?

For image rendering most of the gaming systems install very high end video
cards so that most of the rendering calculations can be off loaded to the
GPU. I am only currently aware of some very specialized and usually custom
applications in image analysis that can take advantage of GPUs. The biggest
bottle necks in image analysis have been memory access. Windows 7 Pro 64
bit allows access to 192 GB of memory so that bottle neck is largely gone.
I would expect the remaining bottle neck to be CPU speed.

My order of preference for maxing performance would be:

1. Enough memory to hold at least two copies of the largest image I
expect to process on a regular basis fully in live memory.
2. Best CPU you can afford, keeping in mind that multithreading
capabilities of the software you will be using. Most image analysis
programs are still single threaded as far as I know.
3. I don't worry too much about SSD's because in my experience image
access time is less of an issue than swapping (which we just eliminated
with 1.). Instead I would put my money into a decent SATA card with RIAD 5
capability and at least three drives for data integrity. Given that images
are constantly getting bigger and experiments also seem to be getting
bigger (meaning that we are seeing more and more images per experiment) I
would also look for the highest capacity storage solution.
4. Given the number of dialogs most imaging applications have I think
multiple monitors are a given, the only question being two or more?

As for buy vs build, my general rule of thumb is if the computer is at
least 50% mine then I will build it; if it is less than 50% mine then I
will buy one from a major vendor and include a service contract in the
purchase so I don't have to support it. Keeping in mind that the more other
people use a computer the less I know about what is happening on the
computer and the harder it is for me to support.

Chris Tully
Microscopy and Image Analysis Expert
[hidden email]
[hidden email]
240-475-9753 (c)

[image: View my profile on LinkedIn]<http://www.linkedin.com/in/christully/>

On Fri, Mar 8, 2013 at 12:24 PM, 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
> *****
>
> 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]
>

Craig Brideau

Re: Computer for image analysis

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
*****

Our primary image processing suite is written for Mac, so we usually just
buy Mac Pros for our heaviest lifting since our in-house software benefits
the most from multiple cores. For secondary purposes, we do have some
PC-only software and I have built several systems for our lab and other
colleagues for running NIS Elements (Nikon), or Olivia (Olympus).
Generally a good i7 with as much RAM as possible is the way to go. Either
16 or 32 GB is quite feasible these days. Since most PCs have four memory
slots you have to choose between 4x4GB for 16 GB total, or 4x8GB for 32 GB
total. Since the 8GB memory modules (DIMMS) are at a slight price premium
right now 32 GB is still a bit expensive, but 16 GB is quite affordable.
A few other considerations:

Ports on the Motherboard: Does it have USB3.0/eSata/Firewire800/Gigabit
Ethernet/whatever you use in-house to move your data around?
Card Slots: Are you going to use GPU (video-card) acceleration? If so make
sure you have the PCI-e slots on the motherboard to socket in multiple
video cards.
Case Size and Front Ports: Does the case have plenty of room internally,
with a good layout for routing cables without getting in the way of fans,
cards, or drives? Does the front of the case have the kind of ports you
would want easy access to so you are not always climbing behind the
computer to plug in your portable hard drive?
Power Supply: Don't skimp on wattage, especially if you are going the
multiple-video-card route. Your processor will also draw extra power when
it runs in turbo (i7's have scalable clock speeds, so they run faster and
suck more power when demand increases)
Cooling: An aftermarket processor fan module is probably a good idea as it
will allow your chip to run in turbo more often with less risk, especially
if the room has questionable ventilation. Make sure your case is large
enough to house the fan and run cables around it. If you have multiple
hard disks putting a large-diameter fan in the case in front of them is
often a good idea.
Solid State Drive: Get a medium-sized (250-500GB) Solid State drive to
install the operating system on and all your programs. You should also
have space left over to act as 'scratch' space when you are manipulating an
image. Move the file over to regular hard-drives when you are done working
on it.
Monitor: Make sure you can actually see what you are working on without
burning out your retinas. A good price/color/brightness compromise is
Samsung's SA850. It has good color reproduction and some nice features to
help reduce eye fatigue, etc. We have a couple of them and they are very
nice to work on.
Keyboard/navigational peripherals: Ergonomic/comfortable mouse is a must.
For working with 3D stacks some sort of 3-D manipulator device like
the 3dconnexion MAY be useful for you. If you are working in the dim, a
keyboard with backlit keys can be useful.

And that's my 2-cents.

Craig

On Fri, Mar 8, 2013 at 10:24 AM, Arvydas Matiukas <[hidden email]>wrote:

Vitaly Boyko

Re: Computer for image analysis

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
*****

It all depends on what kind of image analysis is prevalent in your facility, and what is the largest file (image data set) you are working with (deconvolution, 3D/4D image analysis).
Workstation is what you need. You can get the right one from Dell of HP outlet, the rest could be added (LSI RAID controller/HBA, RAM, graphics, etc). You may need dual processor if you use Parallel Computing TB.

If you need more specifics, please contact me offline.

Vitaly
240-342-6217

________________________________
From: Arvydas Matiukas <[hidden email]>
To: [hidden email]
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=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/>

>> 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]>

we
>>> can select "frame by frame" or "line by line" aquisition and how
the

Vitaly Boyko

Re: Computer for image analysis

In reply to this post by Craig Brideau

____
*****
To join, leave or search the confocal microscopy listserv, go to:
http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
*****

Mac is not serious.... It has been never Pro... in broad sense

________________________________
From: Craig Brideau <[hidden email]>
To: [hidden email]
Sent: Friday, March 8, 2013 1:33 PM
Subject: Re: Computer for image analysis

*****
To join, leave or search the confocal microscopy listserv, go to:
http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
*****

Our primary image processing suite is written for Mac, so we usually just
buy Mac Pros for our heaviest lifting since our in-house software benefits
the most from multiple cores. For secondary purposes, we do have some
PC-only software and I have built several systems for our lab and other
colleagues for running NIS Elements (Nikon), or Olivia (Olympus).
Generally a good i7 with as much RAM as possible is the way to go. Either
16 or 32 GB is quite feasible these days. Since most PCs have four memory
slots you have to choose between 4x4GB for 16 GB total, or 4x8GB for 32 GB
total. Since the 8GB memory modules (DIMMS) are at a slight price premium
right now 32 GB is still a bit expensive, but 16 GB is quite affordable.
A few other considerations:

Ports on the Motherboard: Does it have USB3.0/eSata/Firewire800/Gigabit
Ethernet/whatever you use in-house to move your data around?
Card Slots: Are you going to use GPU (video-card) acceleration? If so make
sure you have the PCI-e slots on the motherboard to socket in multiple
video cards.
Case Size and Front Ports: Does the case have plenty of room internally,
with a good layout for routing cables without getting in the way of fans,
cards, or drives? Does the front of the case have the kind of ports you
would want easy access to so you are not always climbing behind the
computer to plug in your portable hard drive?
Power Supply: Don't skimp on wattage, especially if you are going the
multiple-video-card route. Your processor will also draw extra power when
it runs in turbo (i7's have scalable clock speeds, so they run faster and
suck more power when demand increases)
Cooling: An aftermarket processor fan module is probably a good idea as it
will allow your chip to run in turbo more often with less risk, especially
if the room has questionable ventilation. Make sure your case is large
enough to house the fan and run cables around it. If you have multiple
hard disks putting a large-diameter fan in the case in front of them is
often a good idea.
Solid State Drive: Get a medium-sized (250-500GB) Solid State drive to
install the operating system on and all your programs. You should also
have space left over to act as 'scratch' space when you are manipulating an
image. Move the file over to regular hard-drives when you are done working
on it.
Monitor: Make sure you can actually see what you are working on without
burning out your retinas. A good price/color/brightness compromise is
Samsung's SA850. It has good color reproduction and some nice features to
help reduce eye fatigue, etc. We have a couple of them and they are very
nice to work on.
Keyboard/navigational peripherals: Ergonomic/comfortable mouse is a must.
For working with 3D stacks some sort of 3-D manipulator device like
the 3dconnexion MAY be useful for you. If you are working in the dim, a
keyboard with backlit keys can be useful.

And that's my 2-cents.

Craig

On Fri, Mar 8, 2013 at 10:24 AM, Arvydas Matiukas <[hidden email]>wrote:

Arvydas Matiukas

Re: Computer for image analysis

In reply to this post by Vitaly Boyko

*****
To join, leave or search the confocal microscopy listserv, go to:
http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
*****

Vitaly,

The largest image data set my customers ever showed me was 1GB. I myself
once acquired 3GB dataset. Typical datasets are ~100MB but we
plan to start doing live animal imaging which would produce much
larger files.

Regarding workstation there are few issues to consider:
1) my microscopy core will move soon to the
new research building, and one of my neighbours
will be a modelling core hosting powerful workstations
and servers
2) I am more a hardware than software man, and computer
for me has to be a "modern oscilloscope" as well.
3) I am not doing whole-day image analysis but
typically just trying/figuring out efficient algorithms/solutions
for the core customers.

While reading postings I was able to put together following computer:
=============================================
Thermaltake VN300M1W2N Chaser MK-I Full Tower Gaming Case - ATX, Micro ATX,
4x Ext 5.25", 6x Int 3.5", 2x 200mm Fans, 1x 140mm Fan, 2x USB 3.0 Ports,
2x USB 2.0 Ports, 1x eSATA Port, Colorshift Fans(29.1 lbs) $150

Ultra LSP750 750-Watt Power Supply - ATX, SATA-Ready, SLI-Ready, 135mm Fan,
Lifetime Warranty w/ Registration (5.4 lbs) $70

ASUS Sabertooth 990FX AMD AM3+ TUF Motherboard - ATX, Socket AM3+,
AMD 990FX Chipset, 1866MHz-DDR3, SATA 6.0 Gb/s, RAID, 8-CH Audio,
Gigabit LAN, SuperSpeed USB 3.0, SLI/CrossFireX Ready(4.25 lbs) $185

AMD FD8350FRHKBOX FX-8350 Eight-Core 4GHz AM3+ Processor - AM3+,
Eight-Core, 4GHz, 16MB, 125W, Unlocked (1.3 lbs) $185

16GB, 2x Kingston HyperX Blu KHX1600C10D3B1/8G 8GB Desktop Memory Module
- DDR3, 1600MHz, CL10, DIMM, 240 Pin(0.2 lbs) $90

Corsair Hydro Series CW-9060009-WW H100i Extreme Liquid/Water CPU Cooler
- 2 x 120mm Fan, Multi-socket Support, built-in Corsair Link(4 lbs) $120

Intel SSDSC2CW120A3K5 520 Series Solid State Drive - 120GB, SATA III (6Gb/s),
2.5", up to 550MB/s Read, up to 500MB/s Write, Retail(0.8 lbs) $150

RAID, 3x WD Black 500 GB Internal Hard Drive - 3.5" Form Factor, SATA III 6Gb/s,
64MB Cache, 7200 RPM, RoHS Compliant (WD5003AZEX)(0.3 lbs) $225
EVGA GeForce GT 610 01G-P3-2616-KR Video Card - 1GB, GDDR3, PCI-Express 2.0 (x16), 2x Dual-link DVI, 1x Mini-HDMI, DirectX 11, $37

Microsoft Windows 7 Professional FQC-04649 Operating System Software
- 64bit, DVD(0.4 lbs), $140

======== Computer TOTAL ~$1400 =================

Any comments welcome,
Arvydas

>>> Vitaly Boyko <[hidden email]> 3/8/2013 2:00 PM >>>
*****
To join, leave or search the confocal microscopy listserv, go to:
http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
*****

It all depends on what kind of image analysis is prevalent in your facility, and what is the largest file (image data set) you are working with (deconvolution, 3D/4D image analysis).
Workstation is what you need. You can get the right one from Dell of HP outlet, the rest could be added (LSI RAID controller/HBA, RAM, graphics, etc). You may need dual processor if you use Parallel Computing TB.

If you need more specifics, please contact me offline.

Vitaly
240-342-6217

________________________________
From: Arvydas Matiukas <[hidden email]>
To: [hidden email]
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=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/>

>> 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]>

we
>>> can select "frame by frame" or "line by line" aquisition and how
the

Paul Herzmark

Re: Computer for image analysis

*****
To join, leave or search the confocal microscopy listserv, go to:
http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
*****

A detail to keep in mind if you use Matlab for image analysis. The
Macintosh version of Matlab cannot write and Excel spreadsheet, just comma
separated values (csv file). On a PC it will write normal Excel files.

Paul Herzmark
Specialist
Department of Molecular and Cell Biology
479 Life Science Addition
University of California, Berkeley
Berkeley, CA 94720-3200
(510) 643-9603

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 >>>
>

Oliver Biehlmaier-2

Re: Computer for image analysis

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
*****

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
> *****
>
> 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" <[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
>> ----------------------------------------------------------------
>>
>> _________________
>> From: Arvydas Matiukas <[hidden email]<mailto:[hidden email]>>
>> To:=20
>> [hidden email]<mailto:[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
>> *****
>>
>> 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)
> **********************************************************************

Craig Brideau

Re: Computer for image analysis

*****
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" <[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
> > *****
> >
> > 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" <[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
> >> ----------------------------------------------------------------
> >>
> >> _________________
> >> From: Arvydas Matiukas <[hidden email]<mailto:
> [hidden email]>>
> >> To:=20
> >> [hidden email]<mailto:
> [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
> >> *****
> >>
> >> 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)
> > **********************************************************************
>

George McNamara

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 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"<[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
>>> *****
>>>
>>> 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"<[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
>>>> ----------------------------------------------------------------
>>>>
>>>> _________________
>>>> From: Arvydas Matiukas<[hidden email]<mailto:
>>>>
>> [hidden email]>>
>>
>>>> To:=20
>>>> [hidden email]<mailto:
>>>>
>> [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
>>>> *****
>>>>
>>>> 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)
>>> **********************************************************************
>>>
>>
>

Craig Brideau

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
*****

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)
>>>> ****************************************************************
>>>> **********
>>>>
>>>>
>>>
>>>
>>
>>
>

Arvydas Matiukas

Re: Computer for image analysis ... SSD PCI-e cards, great, die catastrophically, may have have trouble finding an optimized O.S. driver

In reply to this post by George McNamara

*****
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)
>>>> ****************************************************************
>>>> **********
>>>>
>>>>
>>>
>>>
>>
>>
>

Watkins, Simon C

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 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)
>>>>> ****************************************************************
>>>>> **********
>>>>>
>>>>>
>>>>
>>>>
>>>
>>>
>>