[Wien] inefficiency of lapw2 on clusters
Fan
fxinwei123 at gmail.com
Mon Dec 28 13:53:04 CET 2020
Memory should be fine since I have chosen an idle node to do the tests and
I have tested a few omp_global values, it still performed badly. So, it
should be a file/network issue as Prof. Blaha suggested since I
have indeed set the SCRATCH directory as ./. Anyway, thank you for your
suggestions.
Laurence Marks <laurence.marks at gmail.com> 于2020年12月28日周一 下午7:13写道：
> While the server is probably the issue, two other things to check:
> a) lapw2 can need more memory, so swapping issues are not impossible.
> b) How have you set omp_lapw2 ?
>
> _____
> Professor Laurence Marks
> "Research is to see what everybody else has seen, and to think what nobody
> else has thought", Albert Szent-Gyorgi
> www.numis.northwestern.edu
>
> On Mon, Dec 28, 2020, 03:23 Fan <fxinwei123 at gmail.com> wrote:
>
>> Thank you for your quick response. I believe that is the key to the
>> problem. So with larger vector files, the lapw2 will run slower in my
>> situation. That makes sense.
>>
>> Peter Blaha <pblaha at theochem.tuwien.ac.at> 于2020年12月28日周一 下午4:38写道：
>>
>>> This points to a fileserver/network problem on your cluster.
>>>
>>> On a big cluster one usually has a home-directory on a fileserver drive,
>>> which is mounted over a network (eg. NFS, HPFS,..) on all nodes. While
>>> this is very convenient, it is on many systems also a huge bottleneck.
>>> Either the fileserver breaks down due to too many simultaneously
>>> requests or the network does not have sufficient band width.
>>>
>>> You probably have set the SCRATCH variable to your working directory
>>> "./", which means that the large case.vector* files are stored in your
>>> working directory, leading to the bad performance of lapw2.
>>>
>>> On most clusters there is a local scratch or tmp directory (files exist
>>> only on this node) and when setting your SCRATCH variable to this, the
>>> slow lapw2 should be gone.
>>>
>>> In addition, I see that also lapw1 gets only 90% of a core. I recommend
>>> setting OMP_NUM_THREADS=2 and spanning only 4 k-parallel jobs in
>>> parallel (I assume you have a node with 8 cores).
>>>
>>>
>>> On 12/28/20 9:14 AM, Fan wrote:
>>> > Dear wien2k users,
>>> >
>>> > I am trying to run wien2k on clusters, but I encountered a very
>>> strange
>>> > issue that the performance of lapw2 is very inefficient. For example,
>>> >
>>> >
>>> -----------------------------------------------------------------------------------------------------------------------------------------------------------------
>>> > > lapw1 -dn -p (15:27:45) starting parallel lapw1 at Mon Dec
>>> > 28 15:27:46 CST 2020
>>> > -> starting parallel LAPW1 jobs at Mon Dec 28 15:27:46 CST 2020
>>> > running LAPW1 in parallel mode (using .machines.help)
>>> > 8 number_of_parallel_jobs
>>> > f02n10(58) 178.212u 3.134s 3:15.91 92.57% 0+0k 0+0io 0pf+0w
>>> > f02n10(58) 180.210u 3.011s 3:19.46 91.86% 0+0k 0+0io 0pf+0w
>>> > f02n10(58) 183.239u 3.019s 3:22.73 91.87% 0+0k 0+0io 0pf+0w
>>> > f02n10(57) 181.113u 2.884s 3:20.20 91.90% 0+0k 0+0io 0pf+0w
>>> > f02n10(57) 178.433u 2.965s 3:18.85 91.22% 0+0k 0+0io 0pf+0w
>>> > f02n10(57) 151.420u 2.756s 2:48.26 91.63% 0+0k 0+0io 0pf+0w
>>> > f02n10(57) 183.799u 3.065s 3:22.58 92.24% 0+0k 0+0io 0pf+0w
>>> > f02n10(57) 185.867u 3.109s 3:27.50 91.07% 0+0k 0+0io 0pf+0w
>>> > Summary of lapw1para:
>>> > f02n10 k=459 user=1422.29 wallclock=1575.49
>>> > 1.034u 1.698s 3:30.15 1.2% 0+0k 472+128io 2pf+0w
>>> > > lapw2 -up -p (15:31:16) running LAPW2 in parallel mode
>>> > f02n10 37.680u 1.597s 6:32.94 10.00% 0+0k 0+0io 0pf+0w
>>> > f02n10 38.841u 1.682s 7:07.57 9.48% 0+0k 0+0io 0pf+0w
>>> > f02n10 38.611u 1.727s 6:51.53 9.80% 0+0k 0+0io 0pf+0w
>>> > f02n10 38.715u 1.728s 6:48.76 9.89% 0+0k 0+0io 0pf+0w
>>> > f02n10 37.847u 1.639s 7:01.08 9.38% 0+0k 0+0io 0pf+0w
>>> > f02n10 38.170u 1.709s 6:45.01 9.85% 0+0k 0+0io 0pf+0w
>>> > f02n10 39.261u 1.727s 7:01.11 9.73% 0+0k 0+0io 0pf+0w
>>> > f02n10 39.772u 1.765s 7:04.40 9.79% 0+0k 0+0io 0pf+0w
>>> >
>>> >
>>> -----------------------------------------------------------------------------------------------------------------------------------------------------------------
>>> > As you can see the cpu utilizations are much lower than that of lapw1,
>>> > which made lawp2 more time-consuming than lapw1. MPI parallelization
>>> > performed even worse.
>>> >
>>> > More strangely, it seems to be case-dependent. For TiC and some other
>>> > systems, it works fine. I also tried other nodes, the problem still
>>> > persists, however in my local workstation everything went well.
>>> >
>>> > The version of wien2k is 19.2 compiled with intel icc and ifort
>>> without
>>> > any errors. MPI, FFTW, and ELPA are all available.
>>> >
>>> > Any suggestion will be appreciated.
>>> >
>>> > Fan
>>> >
>>> >
>>> >
>>> >
>>> >
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>>>
>>> --
>>>
>>> P.Blaha
>>>
>>> --------------------------------------------------------------------------
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