Thank you for the reply. what I mean by massively parallel processing is
"compute intensive" problem where I will be able to process on many
hosts independently in parallel (by parallelizing the algorithms).
Apologies if I'm repeating what you already know. Currently there are 9
hosts on Beowulf cluster in Lab running on UltraSPARC 5 (yes, very old
machines!).
"raw data" I'm looking for are the input files required for the
application, so I can "process" them. I do not have any specific
application in mind. I will be developing the different components of
the application such as job scheduling, fault tolerance, fault recovery,
etc for my dissertation. I will be useing PVM or MPI for message passing
and programming in c.
But I do have any specific application in mind and I don't mind any
application. I can come up with say, "data mining" but it's pointless
unless I have the "raw data" files to process and know the patterns I'm
looking for.
Application design and programming model all depends on the type of
application I get my hands on. I'm quite desperate for a "problem" since
I have to submit my proposal end of next week. Any help would he greatly
appreciated. I'm sure everyone here has lot of experience in distributed
processing and hopefully can be of some help. Sorry for the long post.
Thanks,
Mitchell
Douglas Eadline wrote:
You may want to quantify "massively parallel"
and define "raw data" (i.e. how many
processors and data for which specific application?)
--
Doug
Hi all,
As part of my dissertation, I'm looking for "raw data" which will be
used for massive parallel processing using Beuwulf cluster (with the use
of PVM or MPI). I tried looking for e-science raw data (and the
computations required on it) such as bioinformatics, fluid dynamics,
etc. but without any luck.
Anyone has any idea of getting some raw data so I can give compute
intensive "work" to the nodes?
Any pointers/hints/tips would be very much appriciated.
Best wishes,
Mitchell
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Doug
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