[Beowulf] dual-core benefits?
Michael Will
mwill at penguincomputing.com
Thu Sep 22 11:35:10 PDT 2005
Possible. The quad-dual core chassis starts at around $7k, with
the 865 that is about $12k, and if you add the 32G of RAM
you look at something just below $20k with 8 cores that fits into 3U.
Michael
Joel Jaeggli wrote:
> On Thu, 22 Sep 2005, Michael Will wrote:
>
>> Tahir wrote that they need 4G per node now and 16G later.
>>
>> If you have dual single core, you have 8G per core, but if
>> you have dual dual core, you only have 4G per core.
>>
>> On the other hand the scalability issues Tahir mentioned below
>> sounds like that interprocess communication is the bottleneck
>> and then you want as many cores as you can get in the system.
>>
>> You could then architect your solution with quad-dual-core opteron
>> systems which gives you 8 cores and 32G of RAM in one node.
>
>
> I suspect that once it's cost effective for you make the jump to 8xx
> cpu's and a non-commidity 4-way mainboard that going all the way to
> the 8way 16 core box is also cost effective.
>
> the iwill h8501 chassis is around $10500 and the opteron 865 are about
> 1,300 ea which is a premium of about $500 over the 265. so probably
> $30k for 16core box that fits in 5u.
>
>> Michael
>>
>>
>>
>>
>> Joe Landman wrote:
>>
>>> Hi Tahir:
>>>
>>> Tahir Malas wrote:
>>>
>>>> Hi everyone,
>>>>
>>>> I would like to take advice for the processor selection for the
>>>> cluster that
>>>> we will configure soon. Comparing the sequential performance of our
>>>> programs
>>>> on an Opteron 246 and a much more expensive machine with Itanium
>>>> Processor,
>>>> we have decided to use opteron processors with Tyan mbs. However,
>>>> we are in
>>>> a confusion to decide on the processor selection. Before posing my
>>>> questions, I'd better give some info about our application
>>>> requirements:
>>>>
>>>> 1. The scalability of our program is not so good, less then 20 for
>>>> 32 nodes
>>>> (measured on a single node system). So we don't plan to go beyond
>>>> 16 nodes.
>>>> (which makes 32 processors due to dual-node usage)
>>>
>>>
>>>
>>> Do you mean a single cpu per node, or single core per CPU, or a
>>> large SMP? You might also wish to look at the iWill motherboards.
>>>
>>>> 2. Memory requirement is huge; we will use 4GB memory per node for
>>>> the time
>>>> being and increase this to 16 GB later. So wee need fast CPUs and
>>>> efficient
>>>> usage of memory.
>>>
>>>
>>>
>>> Ok, you are going to want the later model MB's that properly support
>>> DDR/400 to single rank dimms. 2GB dimms are still not cheap (at
>>> least the good ones).
>>>
>>>> 3. Due to budget limitations we will first configure 8-node system
>>>> with 4GB
>>>> RAM per node and extend this to a 16-node system with 16-GB of RAM
>>>> in 6
>>>> months.
>>>>
>>>> We were thinking of AMD 250 processors, but now the benchmarks of
>>>> dual-core
>>>> CPUs (on the web site of AMD) seems encouraging, and the cost of
>>>> dual-core
>>>> AMD 275 seems to be less then twice of AMD 250.
>>>
>>>
>>>
>>> http://enterprise2.amd.com/downloadables/Dual_Core_Performance.pdf
>>> and other I presume. :)
>>>
>>>> Since the memory cost of our
>>>> system will dominate other costs, we can afford to pass to dual-core
>>>> technology. However, the questions that arise are follows.
>>>>
>>>> 1. Will it worth? And can we gain any advantages over single-core
>>>> with the
>>>> not-so-good scalability of our parallel programs?
>>>
>>>
>>>
>>> It depends upon the code. If your code requires very low latency,
>>> the benefit of dual core nodes are that you have 4 interconnected
>>> cores (think of them as individual processors) connected over a very
>>> high speed low latency interface. If this is well coupled to the
>>> rest of the system through an external low latency interface
>>> (Infinipath, IB, Myrinet, etc), and your code is latency sensitive,
>>> then dual core could be a substantial win for you. If your code
>>> simply hammers on memory bandwidth, then it is possible in some
>>> cases for it to be a liability relative to single core. Some cases
>>> (weather codes) demonstrated something like this here in the recent
>>> past.
>>>
>>>> 2. Another question is that is dual-core technology brings any
>>>> advantages
>>>> for the efficient usage of high amount of memory that we will
>>>> utilize? 3. 3.
>>>
>>>
>>>
>>> Not really advantage or disadvantage. With single core, your
>>> aggregate memory bandwidth is N(cores) * Bandwidth of one of the
>>> memory busses. With dual core, it is (N(cores)/2) * Bandwidth of one
>>> of the memory busses. This may or may not be an issue for your code.
>>>
>>>> 3. Finally there is something basic that I'm not sure: When we
>>>> assign a job
>>>> to dual-core CPU, can it divide it between the core-CPUs
>>>> automatically, or
>>>> should we think dual-core CPU the same as dual-node CPU? If the
>>>> latter is
>>>> the case, what is the advantage of this technology over dual-node?
>>>
>>>
>>>
>>> Think of this as 2 physicallly independent CPUs (that just happen to
>>> share the same space on the motherboard). That means your dual CPU
>>> nodes become 4-ways. In terms of assinging a job to a CPU (or
>>> core), you still need a threading library or an MPI library and
>>> appropriate changes to the source code to make it scale. But the
>>> advantage for you would be less overall latency between CPUs for
>>> messaging using MPI, and large SMP nodes for OpenMP. The potential
>>> disadvantage is loss of effective memory bandwidth. If you look at
>>> the above URL for the paper, you will see that the bandwidth issue
>>> wasn't a factor for the tests we ran. It could be for your code,
>>> and that the important part. You need to test to be sure.
>>>
>>>>
>>>> If anyone has info and/or experiences about these, I will be very
>>>> glad to
>>>> know.
>>>> Thanks in advance,
>>>> Tahir Malas
>>>> Bilkent University Electrical and Electronics Engineering Department
>>>> Phone: +90 312 290 1385
>>>>
>>>>
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>>>
>>>
>>>
>>
>>
>>
>
--
Michael Will
Penguin Computing Corp.
Sales Engineer
415-954-2822
415-954-2899 fx
mwill at penguincomputing.com
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