http://imagej.273.s1.nabble.com/Parallel-image-processing-using-ImageJ-in-the-Cloud-tp3685113p3685120.html
In out tests for parallel image processing with ImageJ on Amazon Could (as
posters. To do "Reduce" step we need to known when process is done
drives not to mention buckets) so this fact has to be considered.
Vitali.
> On Wed, Apr 6, 2011 at 2:00 PM, Gary Sellani <
[hidden email]> wrote:
> > I should point out here that 8 core CPUs (AMD bulldozer) are due in June.
> A dual CPU bulldozer would be 16 cores and not depend on the cloud.
> >
> > Basically what is powering the speed increase is the parallel processing,
> not the cloud itself.
> >
>
> Gary's point is right on. The Cloud is just another parallel
> computing platform. Hadoop implements the MapReduce parallel
> processing framework, which has been used successfully in several
> domains.
>
> Sometimes a problem is not CPU bound. It may be limited by the amount
> of memory or disk on a single machine. In those cases, having more
> cores on a single processor is not going to help. We ran into this
> problem when we were parallelizing a decision tree training algorithm,
> where it requires the training samples to be in memory.
>
> Jimmy
>
> > -----Original Message-----
> > From: Dean Kossives <
[hidden email]>
> > Sender: ImageJ Interest Group <
[hidden email]>
> > Date: Wed, 6 Apr 2011 16:18:23
> > To: <
[hidden email]>
> > Reply-To: ImageJ Interest Group <
[hidden email]>
> > Subject: Re: Parallel image processing using ImageJ in the Cloud
> >
> > Every now and then something comes along that catches my eye. A
> > reduction in processing time from 5 hours to 15 min is great.
> >
> > 1) can you get the processing time down to under 1 minute?
> >
> > Dean P. Kossives
> > Principal Engineer
> > Clear Align
> > 2550 Boulevard of the Generals, Suite 280
> > Eagleville, PA 19403
> > phone 484 956 0510 X185
> > fax 484 956 0511
> > mailto:
[hidden email]
> > www.clearalign.com
> >
> > Clear Align is certified as a SB, 8(a) SDB & WOSB.
> > See us at SPIE Defense, Security, and Sensing (Booth 1017), April 25-29,
> > 2011
> >
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> >
> > -----Original Message-----
> > From: ImageJ Interest Group [mailto:
[hidden email]] On Behalf Of
> > Johannes Schindelin
> > Sent: Wednesday, April 06, 2011 6:25 AM
> > To:
[hidden email]
> > Subject: Re: Parallel image processing using ImageJ in the Cloud
> >
> > Hi Jimmy,
> >
> > On Mon, 4 Apr 2011, Jimmy Su wrote:
> >
> >> We recently completed a Phase 1 SBIR project with OSD on the topic of
> >> analytic tools in the Cloud.
> >
> > I only understood half the words in that sentence, but I'm quite used to
> >
> > that :-)
> >
> >> To demonstrate our tool's ability to construct image processing
> > workflow
> >> and deploy the generated code to the Cloud, we took ImageJ and added
> >> some Cloud processing capabilities by using the MapReduce framework.
> >
> > What exactly did you do in terms of image processing? Some Gaussian
> > Blur,
> > or Find Edges, or some advanced plug-in? From a technical point of view,
> >
> > there are huge differences there.
> >
> >> We added Cloud processing capability to ImageJ by adding a Hadoop
> >> InputFormat to handle image types in HDFS (Hadoop Distributed File
> >> System) and encapsulating ImageJ operations in map and reduce methods.
> >
> > That is_very_ interesting. For a long time I have been wanting to play
> > with Hadoop now.
> >
> >> This significantly increases ImageJ's throughput in processing
> >> images. Attached is the running time chart showing processing time
> >> decreases from over 5 hours on two nodes to 15 minutes on 64 nodes on
> >> Amazon EC2. Are there any interests in the ImageJ community for
> >> parallel processing in the Cloud? What kind of applications are you
> >> developing that needs ImageJ processing in the Cloud? We would love
> >> to hear your feedback.
> >
> > Two feedbacks from my side:
> >
> > 1) fantastic!
> > 2) where can I get it?
> >
> > Ciao,
> > Johannes
> >
>