Re: Parallel image processing using ImageJ in the Cloud

Posted by Gary Sellani on Apr 06, 2011; 9:00pm
URL: http://imagej.273.s1.nabble.com/Parallel-image-processing-using-ImageJ-in-the-Cloud-tp3685113p3685118.html

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.

-----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
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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