Well Mark, don't give up!
I am not sure which one is your application domain, but if you require
24x7 computation, then you should not be hosting that at home.
On the other hand, if you are not doing real computation and you just
have a testbed at home, maybe for debugging your parallel applications
or something similar, you might be interested in a virtualized solution.
Several years ago, I used to "debug" some neural networks at home, but
training sessions (up to two weeks of training) happened at the university.
I would suggest to do something like that.
You can always scale-down your problem in several phases and save the
complete data-set / problem for THE RUN.
You are not being a heretic there, but suffering energy costs ;-)
In more places that you may believe, useful computing nodes are being
replaced just because of energy costs. Even in some application domains
you can even loose computational power if you move from 4 nodes into a
single quad-core (i.e. memory bandwidth problems). I know it is very
nice to be able to do everything at home.. but maybe before dropping
your studies or working overtime to pay the electricity bill, you might
want to reconsider the fact of collapsing your phisical deploy into a
single virtualized cluster. (or just dispatch several threads/processes
in a single system).
If you collapse into a single system you have only 1 mainboard, one HDD,
one power source, one processor (physically speaking), .... and you can
achieve almost the performance of 4 systems in one, consuming the power
of.... well maybe even less than a single one. I don't want to go into
discussions about performance gain/loose due to the variation of the
hardware architecture. Invest some bucks (if you haven't done that yet)
in a good power source. Efficiency of OEM unbranded power sources is
realy pathetic. may be 45-50% efficiency, while a good power source
might be 75-80% efficient. Use the energy for computing, not for heating
your house.
What I mean is that you could consider just collapsing a complete
"small" cluster into single system. If your application is CPU-bound and
not I/O bound, VMware Server could be an option, as it is free software
(unfortunately not open, even tough some patches can be done on the
drivers). I think it is not possible to publish benchmarking data about
VMware, but I can tell you that in long timescales, the performance you
get in the host OS is similar than the one of the guest OS. There are a
lot of problems related to jitter, from crazy clocks to delays, but if
your application is not sensitive to that, then you are Ok.
Maybe this is not a solution, but you can provide more information
regarding your problem before quitting...
my 2 cents....
ariel
Mark Kosmowski escribió:
At some point there a cost-benefit analysis needs to be performed. If
my cluster at peak usage only uses 4 Gb RAM per CPU (I live in
single-core land still and do not yet differentiate between CPU and
core) and my nodes all have 16 Gb per CPU then I am wasting RAM
resources and would be better off buying new machines and physically
transferring the RAM to and from them or running more jobs each
distributed across fewer CPUs. Or saving on my electricity bill and
powering down some nodes.
As heretical as this last sounds, I'm tempted to throw in the towel on
my PhD studies because I can no longer afford the power to run my
three node cluster at home. Energy costs may end up being the straw
that breaks this camel's back.
Mark E. Kosmowski
From: "Jon Aquilina" <[EMAIL PROTECTED]>
not sure if this applies to all kinds of senarios that clusters are used in
but isnt the more ram you have the better?
On 6/30/08, Vincent Diepeveen <[EMAIL PROTECTED]> wrote:
Toon,
Can you drop a line on how important RAM is for weather forecasting in
latest type of calculations you're performing?
Thanks,
Vincent
On Jun 30, 2008, at 8:20 PM, Toon Moene wrote:
Jim Lux wrote:
Yep. And for good reason. Even a big DoD job is still tiny in Nvidia's
scale of operations. We face this all the time with NASA work.
Semiconductor manufacturers have no real reason to produce special purpose
or customized versions of their products for space use, because they can
sell all they can make to the consumer market. More than once, I've had a
phone call along the lines of this:
"Jim: I'm interested in your new ABC321 part."
"Rep: Great. I'll just send the NDA over and we can talk about it."
"Jim: Great, you have my email and my fax # is..."
"Rep: By the way, what sort of volume are you going to be using?"
"Jim: Oh, 10-12.."
"Rep: thousand per week, excellent..."
"Jim: No, a dozen pieces, total, lifetime buy, or at best maybe every
year."
"Rep: Oh...<dial tone>"
{Well, to be fair, it's not that bad, they don't hang up on you..
Since about a year, it's been clear to me that weather forecasting (i.e.,
running a more or less sophisticated atmospheric model to provide weather
predictions) is going to be "mainstream" in the sense that every business
that needs such forecasts for its operations can simply run them in-house.
Case in point: I bought a $1100 HP box (the obvious target group being
teenage downloaders) which performs the HIRLAM limited area model *on the
grid that we used until October 2006* in December last year.
It's about twice as slow as our then-operational 50-CPU Sun Fire 15K.
I wonder what effect this will have on CPU developments ...
--
Toon Moene - e-mail: [EMAIL PROTECTED] - phone: +31 346 214290
Saturnushof 14, 3738 XG Maartensdijk, The Netherlands
At home: http://moene.indiv.nluug.nl/~toon/
Progress of GNU Fortran: http://gcc.gnu.org/ml/gcc/2008-01/msg00009.html
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Jonathan Aquilina
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