15%
05.11.2018
Name=slurm-node-0[0-1] Gres=gpu:2 CPUs=10 Sockets=1 CoresPerSocket=10 \
ThreadsPerCore=1 RealMemory=30000 State=UNKNOWN
PartitionName=compute Nodes=ALL Default=YES MaxTime=48:00:00 DefaultTime=04:00:00 \
Max
15%
16.07.2015
tools.
For example, assume you have three versions of the GNU compiler – 4.8, 4.9, and 5.1 – and the latest Intel and PGI compilers, along with the latest MPICH (3.1.4) and OpenMPI (1.8.5). Altogether
15%
20.02.2023
:
$ ls -s
total 12
4 gpu_test.sh 4 run_gpu_test.sh 4 test_gpu_job_28.log
The job ran successfully with the correct output (Figure 3).
Figure 3: Logfile
15%
30.11.2025
YZCD
03 # DaemonOpts: -f /var/log/collectl -r00:00,7 -m -F60 -s+YZCD --iosize
04 ################################################################################
05 # Collectl: V3.6.1-4 HiRes: 1 Options
15%
08.04.2014
| elapsed: 0.0s remaining: 4.5s
[Parallel(n_jobs=2)]: Done 198 out of 1000 | elapsed: 1.2s remaining: 4.8s
[Parallel(n_jobs=2)]: Done 399 out of 1000 | elapsed: 2.3s remaining: 3.5s
15%
30.11.2025
magazine [3].
In other words, the many Cobbler system records are really the biggest problem. Just to jog your memory: Using system records, Cobbler can create an individual PXE configuration file for each
15%
25.03.2020
7 1 56008 loop1
06 7 2 56184 loop2
07 7 3 91264 loop3
08 259 0 244198584 nvme0n1
09 8 0 488386584 sda
10 8 1 1024 sda1
11
15%
30.11.2020
):
11
12 s = 0.0
13 s += h * f(a)
14 for i in range(1, n):
15 s += 2.0 * h * f(a + i*h)
16 # end for
17 s += h * f(b)
18 return (s/2.)
19 # end def
20
21
22 # Main section
23 comm = MPI
15%
20.05.2014
)]: Done 1 out of 181 | elapsed: 0.0s remaining: 4.5s
[Parallel(n_jobs=2)]: Done 198 out of 1000 | elapsed: 1.2s remaining: 4.8s
[Parallel(n_jobs=2)]: Done 399 out of 1000 | elapsed: 2.3
14%
21.01.2020
7 1 56008 loop1
06 7 2 56184 loop2
07 7 3 91264 loop3
08 259 0 244198584 nvme0n1
09 8 0 488386584 sda
10 8 1 1024 sda1
11
