Zeus HPC is operational. DataLake machine is still experiencing some problems.
Alex
Zeus HPC is operational. DataLake machine is still experiencing some problems.
Alex
Update on the HPC issue:
Temperature in main HPC room stabilised, I brought login nodes and main server and file servers up. Until further update from Estates about the cooling system stability in the room, most of the compute nodes in that room will be offline (that includes new Broadwell nodes)
I brought some Nehalem (half of 8-CPU nodes) and Sandybridge (12-CPU “GPU” queue) compute nodes up in unaffected by cooling failure room (zeus[100-171], zeus[200-217]), they can be used as file servers now are operational.
Regards,
Alex
Hi,
Zeus HPC is down due to cooling failure in the room EC3-23.
Regards,
Alex
P.S. will update you when it can come back….
Important Information for Existing MATLAB and Simulink Users
Faculty of Environment, Engineering and Computing at Coventry University now offers a campus-wide license to MATLAB, Simulink, and companion toolboxes (MATLAB TAH Site License). The license covers on-campus and home software use for all instructors, staff, and researchers, as well as classroom and lab installations. Students are also covered by the campus-wide license and can install software on their home or laptop computers.
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Alex Pedcenko
Dear Zeus HPC users
You are receiving this post because you are on the user list of Zeus HPC (http://zeus.coventry.ac.uk). This is test post to check website communications working properly.
You can log in to the Zeus Blog (WordPress) webpage to post create posts in the “HPC Announcements” (a.k.a “HPC News” category). You can also contribute to other sections of Zeus Website (posts will be moderated beforehand)
The login password for WordPress on Zeus was generated randomly for you. You can change it if you like by navigating Zeus WordPress login page http://zeus.coventry.ac.uk/wordpress/wp-login.php and pressing “Lost Password“, you will receive the link to reset your password to your registered e-mail.
Alex Pedcenko
(“World fastest GPU accelerator” as per 2014 — http://images.nvidia.com/content/tesla/pdf/nvidia-tesla-k80-overview.pdf )
10 New Zeus HPC Broadwell-CPU based nodes have 10 x 2 Nvidia Tesla K80 GPU accelerators on board (2 per node). Theoretical performance of each K80 GPU in double precision is 2.91 TFlops (8.7 TFlop in single precision) , which gives theoretical GPU power of these nodes in order of 58 TFlop in double precision calculations.
18 Older Sandybridge CPU-based compute nodes of Zeus have 36 Nvidia Tesla K20 GPU accelerators (2 per node), each of K20 has max. theoretical performance of 1.2 TFlops (double precision), which gives overall max GPU compute power of 43 TFlop. Obviously this is just an indication of the amount of max. possible compute power at ideal scaling (realistically you can’t just add these numbers together).
In comparison HPL benchmark performed on CPUs of all new 56 Broadwell nodes (1792 CPU-cores) gave 34 Tflop and 1152 CPUs of older 8-Core Nehalem based nodes gave 9.5 TFlops. and 18 x 12-core Sandybridge CPUs produced about 3.6 TFlops. See details here: http://zeus.coventry.ac.uk/wordpress/?s=HPL
——
Alex
MPP version of LSDYNA was tested for various CPU configurations on new Broadwell nodes vs old Nehalem 8-CPU nodes for the same problem.
SLURM file for LS-Dyna 9.1.0 submission is here lsdyna.
For 9.1.0 version of LSDYNA use
module load lsdyna/971
module load lsdyna/pmpi
| Family | Nodes | CPUs | EXEC_TIME, hrs | lsdyna ver | mpi |
| Broadwell | 1 | 32 | 06:02 | 7.1.2 | HPMPI |
| Broadwell | 1 | 16 | 09:22 | 7.1.2 | HPMPI |
| Nehalem | 2 | 16=2×8 | >12 hrs (time limit reached) | 7.1.2 | HPMPI |
| Broadwell | 2 | 32=2×16 | 05:28 | 7.1.2 | HPMPI |
| Broadwell | 4 | 64=4×16 | 02:51 | 9.1.0 | PMPI |
| Broadwell | 8 | 128=8×16 | 01:46 | 9.1.0 | PMPI |
| Broadwell | 2 | 64=2×32 | 05:08 | 9.1.0 | PMPI |
| Sandybridge | 2 | 24=2×12 | 09:30 | 7.1.3 | PMPI |
So It looks like running LSDYNA on both CPUs (16 cores) of Broadwell is really does not make the problem solve faster. Instead use just 16 CPU-cores (see 64 CPU-cores case — its 2x faster!): either all on one socket or on different ones is still remains to be tested.
Alex Pedcenko
Below are results of few HPL tests on all 56 new Broadwell 32-CPU nodes as well as on all 144 old Nehalems. Netlib xhpl was compiled with intel icc and ran with Bullx mpi. Here are the results:
| # of cores | CPU model | Config | Flops achieved | theoretical |
| 1792 | Broadwell | 56 nodes | 34 Tflops | 30.1 Tflops |
| 1152 | Nehalem | 144 nodes | 9.5 Tflops | |
| 320 | Broadwell | 10 nodes | 6.523 Tflops | 5.376 Tflops |
| 32 | Broadwell | 1 node | 675 Gflops | 537.6 Gflops |
| 12 | Broadwell | 1 node | 260 Gflops | 202 Gflops |
| 204 | Sandybridge | 17 nodes (from GPU queue) | 3.3 TFlops | 3.9 TFops |
| 12 | Sandybridge | 1 node (from GPU queue) | 200 Gflops | 230 Gflops |
| 8 | Sandybridge | 1 node (48 Gb, 12 CPU-cores) | 135.6 Gflops | 76.7 |
| 8 | Nehalem | 1 node | 70.49 Gflops | 76.6 |
| 8 | Nehalem | 4 nodes x 2 cores | 70.15 Gflops | 76.6 |
| 8 | Sandybridge | 4 nodes x 2 cores | 135.6 Gflops | 76.8 |
| 8 | Nehalem | 2 floors x 2 nodes x 2 cores | 70.17 Gflops | 76.8 |
| 216 | Sandybridge | 18 nodes x 12 cores | 3.5 Tflops | — |
| 576 | Nehalem | 72 nodes x 8 cores | 4.5 Tflops | — |
| 32 | Sandybridges on SMP node | 1 nodes x 32 cores | 0.5 Tflops | — |
Test ran using bullx mpi 1.2.9
#################### 2013 results #######################
Below are some first basic HPL (linpack) results of the cluster.
We have two types of CPU’s on Zeuse’s nodes (both @2.4 GHz):
| # of cores | CPU model | Config | Flops achieved | theoretical |
| 8 | Sandybridge | 1 node | 135.6 Gflops | 76.7 |
| 8 | Nehalem | 1 node | 70.49 Gflops | 76.6 |
| 8 | Nehalem | 4 nodes x 2 cores | 70.15 Gflops | 76.6 |
| 8 | Sandybridge | 4 nodes x 2 cores | 135.6 Gflops | 76.8 |
| 8 | Nehalem | 2 floors x 2 nodes x 2 cores | 70.17 Gflops | 76.8 |
| 216 | Sandybridge | 18 nodes x 12 cores | 3.5 Tflops | — |
| 576 | Nehalem | 72 nodes x 8 cores | 4.5 Tflops | — |
| 32 | Sandybridges on SMP node | 1 nodes x 32 cores | 0.5 Tflops | — |
Test ran using bullx mpi 1.2.4
Alex Pedcenko
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