[Beowulf] raid 1 or ldap?

f.costen@cs.man.ac.uk fumie.costen at manchester.ac.uk
Fri Nov 16 03:26:13 PST 2007


Dear  Reuti,

Reuti wrote:
> Hi,
> 
> Am 13.11.2007 um 10:50 schrieb f.costen at cs.man.ac.uk:
> 
>> I am clustering 8 32-bits machines and 5 64 bits machines.
>> 64 bits machines are heavily used for MPI jobs
>> and rest of the machines are simply being terminal for
>> PhD students.
>> One of 64-bits machine has all the users' home
>> directory and softwares (not kernel)
>> for both 32bits machines and 64 bits machines
>> and it exports these directories to client machines via NFS.
>> About 10 LDAP  users are maintained by the server.
>> This server has 2 external harddisk connected by firewire
>> and these two harddisks are used to store the software and home
>> directories for users under RAID 1 system.
>> We deliverately did NOT use the internal harddisk
>> for the home directory because the internal harddisk (each machine has
>> about 500-750 GB) on each machine
>> can be used for the calculation.
>> Raid 1 slows down the system a bit  but we did not expect any reduction
>> of the speed of calculation using the local harddisk.
>>
>> When I did a very small calculation
>> on my laptop which is standing alone,
>> the execution time was faster than my local cluster machine
>> ( no parallelisation, serial job ).
>>
>> The laptop has the CPU which is 32bit with 1G of memory and has
>> vendor_id       : GenuineIntel
>> model name      : Intel(R) Pentium(R) 4 Mobile CPU 2.00GHz
>> stepping        : 4
>> cpu MHz         : 1994.395
>> cache size      : 512 KB
>> cpuid level     : 2
>> bogomips        : 3992.82
>>
>> The test machine in the cluster has dual core with 4GB of memory and
>> each core has
>> vendor_id       : AuthenticAMD
>> model name      : AMD Athlon(tm) 64 X2 Dual Core Processor 4200+
>> stepping        : 1
>> cpu MHz         : 2200.000
>> cache size      : 512 KB
>> cpuid level     : 1
>> bogomips        : 4404.88
>> TLB size        : 1024 4K pages
>> clflush size    : 64
>> cache_alignment : 64
>> address sizes   : 40 bits physical, 48 bits virtual
>>
>> The same programme and the same compiler option and the same compiler
>> are used for these two machines.
> 
> maybe the program you compiled was optimized to run on Intel CPUs, hence
> perform worse on AMD's. What compiler and what options were used? Even
> any BLAS or LAPACK lib might be optimized for one of the platforms.
> 
> Were other jobs running at the same time on the cluster node?
Many thanks for your feedback.
the compiler was intel fortran. No BLAS/LAPACK involved.
The compilation option I used for Intel
was -CB -fpp -FR -O3 -static -xN -ipo
and for AMD, I used -FR -O3 -static
I thought I was using the same compilation option,
but indeed I was customizing the optimization of intel cpu
under intel. Many thanks for pointing out this which I really
should have thought of.
Best wishes, Fumie



> 
> -- Reuti
> 
>> On the laptop:
>> 174.650u 4.752s 3:01.70 98.7%
>>
>> On the local cluster under /home( i.e., under RAID1)
>> 209.457u 1.116s 4:07.05 85.2%
>>
>> On the local cluster under /local
>> 204.268u 1.696s 3:26.04 99.9%
>>
>> What I can not understand is that
>> under /local area we are supposed to be achieving
>> a good/better performance than the laptop
>> ( at least it was the case when each machine
>> was standing alone  having the home for each user)
>> But this is not the case in reality.
>>
>> When it comes to the situation where we have to run
>> a large job, the difference is not in the order of "second"
>> but  order of "days".
>>
>> I am wondering if any of us in this mailing list
>> has similar experience in the past and if you have,
>> I would like to know how you solved this type of problems.
>> At the moment, I have just transfered the home directories and
>> software directories into the the internal harddisk (discarding the raid
>> 1 system) as a test and when we calculate and produce the
>> results under home directories or under the spare local area of the
>> server, again the system is too slow to bear..
> 
> 
> 



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