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Old 07-27-2012, 02:17 AM   #1
iashkan
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Lightbulb Single System Image (SSI) Cluster help request


Hi all

I have a small cluster network (96 cores).
Cluster management software is oracle grid engine.

this cluster is using for MRI analyses with FSL and Freesurfer and of course matlab on all linux nodes.

now I have a simple problem. oge distribute jobs on computers. it means paralleling. but some of analyzes are very heavy for a single core.

I need some thing to simulate my network as a very big computer. I googled and found SSI solutions. OpenMosix and OpenSSI. sadly it openmosix is off.
OpenSSI i don't know.


1- is any alternative solution?
2- Is SSI means at last I have a big CPU? Is run my analyzes faster?
 
Old 07-27-2012, 07:01 PM   #2
syg00
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1) I don't know of anything like you seem to be describing.
2) NO. SSI is to give the impression of one large computer (rather than your grid of nodes). Nothing can make your cores "bigger" from a process scheduling perspective. At least not yet - maybe some smart researcher is looking at it ...
 
Old 07-27-2012, 11:17 PM   #3
iashkan
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Quote:
Originally Posted by syg00 View Post
2) NO. SSI is to give the impression of one large computer (rather than your grid of nodes). Nothing can make your cores "bigger" from a process scheduling perspective.
thank you for reply
what do you mean by large computer?
large computer can process faster or means just more ram size?
 
Old 07-28-2012, 11:37 AM   #4
btmiller
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SSI means single system image. Basically it means that all your cores, memory, disk, etc. on the network are under the control of a single OS image, so the whole network looks like one big SMP (symmetric-multiprocessor) machine. In theory this machine can process much faster, but only if the software is written to use multiple cores. A more traditional alternative is to use something like MPI to run your software in parallel. You might want to check if any of the programs that you're using have MPI support. Either way, the speed and latency of the network can dramatically impact performance, as your nodes must communicate heavily over it.
 
  


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