Sorry that I didn't make it clear. The dayfile was for cluster B. As I said before, I always request one core per node and 8 nodes per job (number of k points). I have 72 crystallographically non-equivalent atoms.
On cluster B, I used the following R_LIB (LAPACK+BLAS) option to compile WIEN2k. -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -openmp -iomp5 Yundi On Thu, Oct 17, 2013 at 7:50 AM, Laurence Marks <l-ma...@northwestern.edu>wrote: > I assume the dayfile was for cluster A, as wall is about 8x cpu which > is about right for mkl multithreading which you are presumably using. > You are not using mpi. You may want to compare the wall time to using > on cluster A > > 1:node1:8 > > depending upon many factors it may be faster, or slower. This is only > doing mpi using the bus not between nodes. > > Is it 72 unique atoms, or 72 total? > > My guess is that cluster A is about right. You can make it faster by > using iterative diagonalization (-it or -it -noHinv) and perhaps > reducing RKMAX -- you don't say what your RMTs are. > > For cluster B what blas/lapack are you using? Does it really have that > many cores/node or is it using hyperthreading (which does not really > give you much)? How is your NFS structured -- good communications or > just slow ethernet? > > > On Thu, Oct 17, 2013 at 9:33 AM, Yundi Quan <q...@ms.physics.ucdavis.edu> > wrote: > > Thanks for your reply. > > a). both machines are set up in a way that once a node is assigned to a > job, > > it cannot be assigned to another. > > b). The .machines file looks like this > > 1:node1 > > 1:node2 > > 1:node3 > > 1:node4 > > 1:node5 > > 1:node6 > > 1:node7 > > 1:node8 > > granularity:1 > > extrafine:1 > > lapw2_vector_split:1 > > > > I've been trying to avoid using mpi because sometime mpi can slow down my > > calculations because of poor communications between nodes. > > > > c). the amount of memory available to a core does not seem to be the > problem > > in my case because my job could run smoothly on cluster A where each node > > has 8G memory and 8 core). But my job runs into memory problems on > cluster B > > where each core has much more memory available. I wonder whether there > are > > parameters which I should change in WIEN2k to reduce the memory usage. > > > > d). My dayfile for a single iteration looks like this. The wallclocks are > > around 500. > > > > > > cycle 1 (Fri Oct 11 02:14:05 PDT 2013) (40/99 to go) > > > >> lapw0 -p (02:14:05) starting parallel lapw0 at Fri Oct 11 02:14:06 PDT > >> 2013 > > -------- .machine0 : processors > > running lapw0 in single mode > > 1431.414u 22.267s 24:14.84 99.9% 0+0k 0+0io 0pf+0w > >> lapw1 -up -p -c (02:38:20) starting parallel lapw1 at Fri Oct 11 > >> 02:38:20 PDT 2013 > > -> starting parallel LAPW1 jobs at Fri Oct 11 02:38:21 PDT 2013 > > running LAPW1 in parallel mode (using .machines) > > 8 number_of_parallel_jobs > > c1208-ib(1) 26558.265u 17.956s 7:34:14.39 97.5% 0+0k 0+0io 0pf+0w > > c1201-ib(1) 26845.212u 15.496s 7:39:59.37 97.3% 0+0k 0+0io 0pf+0w > > c1180-ib(1) 25872.609u 18.143s 7:23:53.43 97.2% 0+0k 0+0io 0pf+0w > > c1179-ib(1) 26040.482u 17.868s 7:26:38.66 97.2% 0+0k 0+0io 0pf+0w > > c1178-ib(1) 26571.271u 17.946s 7:34:16.23 97.5% 0+0k 0+0io 0pf+0w > > c1177-ib(1) 27108.070u 34.294s 8:32:55.53 88.1% 0+0k 0+0io 0pf+0w > > c1171-ib(1) 26729.399u 14.175s 7:36:22.67 97.6% 0+0k 0+0io 0pf+0w > > c0844-ib(1) 25883.863u 47.148s 8:12:35.54 87.7% 0+0k 0+0io 0pf+0w > > Summary of lapw1para: > > c1208-ib k=1 user=26558.3 wallclock=454 > > c1201-ib k=1 user=26845.2 wallclock=459 > > c1180-ib k=1 user=25872.6 wallclock=443 > > c1179-ib k=1 user=26040.5 wallclock=446 > > c1178-ib k=1 user=26571.3 wallclock=454 > > c1177-ib k=1 user=27108.1 wallclock=512 > > c1171-ib k=1 user=26729.4 wallclock=456 > > c0844-ib k=1 user=25883.9 wallclock=492 > > 97.935u 34.265s 8:32:58.38 0.4% 0+0k 0+0io 0pf+0w > >> lapw1 -dn -p -c (11:11:19) starting parallel lapw1 at Fri Oct 11 > >> 11:11:19 PDT 2013 > > -> starting parallel LAPW1 jobs at Fri Oct 11 11:11:19 PDT 2013 > > running LAPW1 in parallel mode (using .machines.help) > > 8 number_of_parallel_jobs > > c1208-ib(1) 26474.686u 16.142s 7:33:36.01 97.3% 0+0k 0+0io 0pf+0w > > c1201-ib(1) 26099.149u 40.330s 8:04:42.58 89.8% 0+0k 0+0io 0pf+0w > > c1180-ib(1) 26809.287u 14.724s 7:38:56.52 97.4% 0+0k 0+0io 0pf+0w > > c1179-ib(1) 26007.527u 17.959s 7:26:10.62 97.2% 0+0k 0+0io 0pf+0w > > c1178-ib(1) 26565.723u 17.576s 7:35:20.11 97.3% 0+0k 0+0io 0pf+0w > > c1177-ib(1) 27114.619u 31.180s 8:21:28.34 90.2% 0+0k 0+0io 0pf+0w > > c1171-ib(1) 26474.665u 15.309s 7:33:38.15 97.3% 0+0k 0+0io 0pf+0w > > c0844-ib(1) 26586.569u 15.010s 7:35:22.88 97.3% 0+0k 0+0io 0pf+0w > > Summary of lapw1para: > > c1208-ib k=1 user=26474.7 wallclock=453 > > c1201-ib k=1 user=26099.1 wallclock=484 > > c1180-ib k=1 user=26809.3 wallclock=458 > > c1179-ib k=1 user=26007.5 wallclock=446 > > c1178-ib k=1 user=26565.7 wallclock=455 > > c1177-ib k=1 user=27114.6 wallclock=501 > > c1171-ib k=1 user=26474.7 wallclock=453 > > c0844-ib k=1 user=26586.6 wallclock=455 > > 104.607u 18.798s 8:21:30.92 0.4% 0+0k 0+0io 0pf+0w > >> lapw2 -up -p -c (19:32:50) running LAPW2 in parallel mode > > c1208-ib 1016.517u 13.674s 17:11.10 99.9% 0+0k 0+0io 0pf+0w > > c1201-ib 1017.359u 13.669s 17:11.82 99.9% 0+0k 0+0io 0pf+0w > > c1180-ib 1033.056u 13.283s 17:27.07 99.9% 0+0k 0+0io 0pf+0w > > c1179-ib 1037.551u 13.447s 17:31.50 99.9% 0+0k 0+0io 0pf+0w > > c1178-ib 1019.156u 13.729s 17:13.49 99.9% 0+0k 0+0io 0pf+0w > > c1177-ib 1021.878u 13.731s 17:16.07 99.9% 0+0k 0+0io 0pf+0w > > c1171-ib 1032.417u 13.681s 17:26.70 99.9% 0+0k 0+0io 0pf+0w > > c0844-ib 1022.315u 13.870s 17:16.81 99.9% 0+0k 0+0io 0pf+0w > > Summary of lapw2para: > > c1208-ib user=1016.52 wallclock=1031.1 > > c1201-ib user=1017.36 wallclock=1031.82 > > c1180-ib user=1033.06 wallclock=1047.07 > > c1179-ib user=1037.55 wallclock=1051.5 > > c1178-ib user=1019.16 wallclock=1033.49 > > c1177-ib user=1021.88 wallclock=1036.07 > > c1171-ib user=1032.42 wallclock=1046.7 > > c0844-ib user=1022.32 wallclock=1036.81 > > 31.923u 13.526s 18:20.12 4.1% 0+0k 0+0io 0pf+0w > >> lapw2 -dn -p -c (19:51:10) running LAPW2 in parallel mode > > c1208-ib 947.942u 13.364s 16:01.75 99.9% 0+0k 0+0io 0pf+0w > > c1201-ib 932.766u 13.640s 15:49.22 99.7% 0+0k 0+0io 0pf+0w > > c1180-ib 932.474u 13.609s 15:47.76 99.8% 0+0k 0+0io 0pf+0w > > c1179-ib 936.171u 13.691s 15:50.33 99.9% 0+0k 0+0io 0pf+0w > > c1178-ib 947.798u 13.493s 16:04.99 99.6% 0+0k 0+0io 0pf+0w > > c1177-ib 947.786u 13.350s 16:04.89 99.6% 0+0k 0+0io 0pf+0w > > c1171-ib 930.971u 13.874s 15:45.22 99.9% 0+0k 0+0io 0pf+0w > > c0844-ib 950.723u 13.426s 16:04.69 99.9% 0+0k 0+0io 0pf+0w > > Summary of lapw2para: > > c1208-ib user=947.942 wallclock=961.75 > > c1201-ib user=932.766 wallclock=949.22 > > c1180-ib user=932.474 wallclock=947.76 > > c1179-ib user=936.171 wallclock=950.33 > > c1178-ib user=947.798 wallclock=964.99 > > c1177-ib user=947.786 wallclock=964.89 > > c1171-ib user=930.971 wallclock=945.22 > > c0844-ib user=950.723 wallclock=964.69 > > 31.522u 13.879s 16:53.13 4.4% 0+0k 0+0io 0pf+0w > >> lcore -up (20:08:03) 2.993u 0.587s 0:03.75 95.2% 0+0k 0+0io 0pf+0w > >> lcore -dn (20:08:07) 2.843u 0.687s 0:03.66 96.1% 0+0k 0+0io 0pf+0w > >> mixer (20:08:21) 23.206u 32.513s 0:56.63 98.3% 0+0k 0+0io 0pf+0w > > :ENERGY convergence: 0 0.00001 416.9302585700000000 > > :CHARGE convergence: 0 0.0000 3.6278086 > > > > > > On Thu, Oct 17, 2013 at 7:11 AM, Laurence Marks < > l-ma...@northwestern.edu> > > wrote: > >> > >> There are so many possibilities, a few: > >> > >> a) If you only request 1 core/node most queuing systems (qsub/msub > >> etc) will allocate the other cores to other jobs. You are then going > >> to be very dependent upon what those other jobs are doing. Normal is > >> to use all the cores on a given node. > >> > >> b) When you run on cluster B, in addition to a) it is going to be > >> inefficient to run with mpi communications across nodes and it is much > >> better to run on a given node across cores. Are you using a machines > >> file with eight 1: nodeA lines (for instance) or one with a single 1: > >> nodeA nodeB....? The first does not use mpi, the second does. To use > >> mpi within a node you would use lines such as 1:node:8. Knowledge of > >> your .machines file will help people assist you. > >> > >> c) The memory on those clusters is very small, whoever bought them was > >> not thinking about large scale jobs. I look for at least 4G/core, and > >> 2G/core is barely acceptable. You are going to have to use mpi. > >> > >> d) All mpi is equal, but some mpi is more equal than others. Depending > >> upon whether you have infiniband, ethernet, openmpi, impi and how > >> everything was compiled you can see enormous differences. One thing to > >> look at is the difference between the cpu time and wall time (both in > >> case.dayfile and at the bottom of case.output1_*). With a good mpi > >> setup the wall time should be 5-10% more than the cpu time; with a bad > >> setup it can be several times it. > >> > >> On Thu, Oct 17, 2013 at 8:44 AM, Yundi Quan <quanyu...@gmail.com> > wrote: > >> > Hi, > >> > I have access to two clusters as a low-level user. One cluster > (cluster > >> > A) > >> > consists of nodes with 8 core and 8 G mem per node. The other cluster > >> > (cluster B) has 24G mem per node and each node has 14 cores or more. > The > >> > cores on cluster A are Xeon CPU E5620@2.40GHz, while the cores on > >> > cluster B > >> > are Xeon CPU X5550@2.67GH. From the specifications (2.40GHz+12288 KB > >> > cache > >> > vs 2.67GHz+8192 KB cache), two machines should be very close in > >> > performance. > >> > But it does not seem to be so. > >> > > >> > I have job with 72 atoms per unit cell. I initialized the job on > cluster > >> > A > >> > and ran it for a few iterations. Each iteration took 2 hours. Then, I > >> > moved > >> > the job to cluster B (14 cores per node with @2.67GHz). Now it takes > >> > more > >> > than 8 hours to finish one iteration. On both clusters, I request one > >> > core > >> > per node and 8 nodes per job ( 8 is the number of k points). I > compiled > >> > WIEN2k_13 on cluster A without mpi. On cluster B, WIEN2k_12 was > compiled > >> > by > >> > the administrator with mpi. > >> > > >> > What could have caused poor performance of cluster B? Is it because of > >> > MPI? > >> > > >> > On an unrelated question. Sometimes memory would run out on cluster B > >> > which > >> > has 24Gmem per node. Nevertheless the same job could run smoothly on > >> > cluster > >> > A which only has 8 G per node. > >> > > >> > Thanks. > >> > >> > >> > >> -- > >> Professor Laurence Marks > >> Department of Materials Science and Engineering > >> Northwestern University > >> www.numis.northwestern.edu 1-847-491-3996 > >> "Research is to see what everybody else has seen, and to think what > >> nobody else has thought" > >> Albert Szent-Gyorgi > >> _______________________________________________ > >> Wien mailing list > >> Wien@zeus.theochem.tuwien.ac.at > >> http://zeus.theochem.tuwien.ac.at/mailman/listinfo/wien > >> SEARCH the MAILING-LIST at: > >> http://www.mail-archive.com/wien@zeus.theochem.tuwien.ac.at/index.html > > > > > > > > -- > Professor Laurence Marks > Department of Materials Science and Engineering > Northwestern University > www.numis.northwestern.edu 1-847-491-3996 > "Research is to see what everybody else has seen, and to think what > nobody else has thought" > Albert Szent-Gyorgi > _______________________________________________ > Wien mailing list > Wien@zeus.theochem.tuwien.ac.at > http://zeus.theochem.tuwien.ac.at/mailman/listinfo/wien > SEARCH the MAILING-LIST at: > http://www.mail-archive.com/wien@zeus.theochem.tuwien.ac.at/index.html >
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