[Beowulf] Re: Beowulf Digest, Vol 53, Issue 1

Tue Jul 1 13:14:26 PDT 2008

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" <eagles051387 at gmail.com>
>>     
>
>   
>> 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 <diep at xs4all.nl> 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: toon at moene.indiv.nluug.nl - 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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