From: Axel Kohlmeyer (akohlmey_at_gmail.com)
Date: Mon Apr 11 2011 - 15:06:33 CDT
On Mon, Apr 11, 2011 at 3:41 PM, Gianluca Interlandi
<gianluca_at_u.washington.edu> wrote:
>> if you want to go low risk and don't have much experience with GPU, then
>> probably the best deal you can currently get for running NAMD on small
>> problems is to build a "workstation" from 4-way 8-core AMD magny-cours
>> processors. that will be like a small cluster in a box (32-cores total)
>> and
>> you may be able to operate it with 16GB of RAM (although 32GB is probably
>> not that much more expensive and will make it more future proof).
>
> I wonder how NAMD would perform on one of these 48 AMD cores blade:
blades generally tend to be a bit slower than "normal" nodes.
i am attaching some graphs with performance numbers from some local machine(s).
note that the $$$ estimate includes a share of the (rather expensive) QDR
infiniband infrastructure switch and the IB HCAs. that - of course - works
in favor of the 48-core and GPU nodes in the performance per $$ category,
but also reduces their scaling capability.
> http://configure.us.dell.com/dellstore/config.aspx?c=us&cs=555&l=en&oc=MLB1985&s=biz
>
> If you have a 100K budget one could test 2-3 of those and add more later.
why so much memory? that is the main cost for those.
also, never go with the highest clock rate.
i would expect you get the best bang for the buck using
4-way 2.5GHz 8-core with 32GB (even 16GB would do
well for running only NAMD)
axel.
>
> Gianluca
>
>
>>
>> this way, you can save a lot of money by not needing a fast interconnect.
>>
>> the second best option in my personal opinion would be a dual intel
>> westmere processor (4-core) based workstation with 4 GPUs. depending
>> on the choice of GPU, CPU and amount of memory, that may be bit
>> faster or slower than the 32-core AMD. the westmere has more memory
>> bandwidth and you can have 4x 16-x gen2 PCI-e to get the maximum
>> bandwidth to and from the GPUs. when using GeForce GPUs you are
>> taking a bit of a risk in terms of reliability, since there is no easy way
>> to tell, if you have memory errors, but the Tesla "compute" GPUs will
>> bump up the price significantly.
>>
>>> If the funding is approved we will have to built by our own a small
>>> cluster.
>>> There is not many people with expertise around that can help us. Any
>>> suggestion, help or information would be greatly appreciated.
>>
>> there is no replacement for knowing what you are doing and
>> some advice from a random person on the internet, like me,
>> is not exactly what i would call a trustworthy source that i
>> would unconditionally bet my money on. you have to make
>> tests by yourself.
>>
>> i've been designing, setting up and running all kinds of linux
>> clusters for almost 15 years now and despite that experience,
>> _every_ time i have to start almost from scratch and evaluate
>> the needs and match it with available hardware options. one
>> thing that people often forget in the process is that they only
>> look at the purchasing price, but not the cost of maintenance
>> (in terms of time that the machine is not available, when it takes
>> long to fix problems, or when there are frequent hardware failures)
>> and the resulting overall "available" performance.
>>
>> i've also learned that you cannot trust any sales person.
>> they don't run scientific applications and have no clue
>> what you really need or not. similarly for the associated
>> "system engineers" they know very well how to rig and
>> install a machine, but they are never have to _operate_
>> one (and often without expert staff, as usual in many
>> academic settings).
>>
>> so the best you can do is to be paranoid, test for yourself
>> and make sure that the risk you are taking does not outweigh
>> the technical expertise that you have available to operate
>> the hardware.
>>
>> HTH,
>> axel.
>>
>>> Thanks a lot,
>>>
>>> HVS
>>>
>>>
>>>
>>>
>>>
>>
>>
>>
>> --
>> Dr. Axel Kohlmeyer
>> akohlmey_at_gmail.com http://goo.gl/1wk0
>>
>> Institute for Computational Molecular Science
>> Temple University, Philadelphia PA, USA.
>>
>>
>
> -----------------------------------------------------
> Gianluca Interlandi, PhD gianluca_at_u.washington.edu
> +1 (206) 685 4435
> http://artemide.bioeng.washington.edu/
>
> Postdoc at the Department of Bioengineering
> at the University of Washington, Seattle WA U.S.A.
> -----------------------------------------------------
-- Dr. Axel Kohlmeyer akohlmey_at_gmail.com http://goo.gl/1wk0 Institute for Computational Molecular Science Temple University, Philadelphia PA, USA.
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