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UEABS
ueabs
Commits
6abed49d
Commit
6abed49d
authored
Jan 14, 2019
by
Andrew Emerson
Browse files
New job files
parent
a961cabe
Changes
3
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43 additions
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quantum_espresso/DAVIDE/job-gpu.sh
quantum_espresso/DAVIDE/job-gpu.sh
+13
-0
quantum_espresso/Marconi-knl/job
quantum_espresso/Marconi-knl/job
+23
-0
quantum_espresso/README.md
quantum_espresso/README.md
+7
-8
No files found.
quantum_espresso/DAVIDE/job-gpu.sh
0 → 100644
View file @
6abed49d
#!/bin/bash
# script for DAVIDE 16 cores/node
# - 13 nodes, 4 tasks/node, 4 OMP threads/task
# Below <account> represents the budget
#SBATCH -N13
#SBATCH --gres=gpu:4
#SBATCH -A <account>
#SBATCH --tasks-per-node=4
#SBATCH -p dvd_usr_prod
#SBATCH -t 1:00:00
export
OMP_NUM_THREADS
=
4
srun
-v
-np
52 ./pw.x
-input
./Ta2O5.in
-npool
26
quantum_espresso/Marconi-knl/job
0 → 100644
View file @
6abed49d
#!/bin/bash
# Batch file for using the Intel APS trace facility
# on Marconi KNL
#
#SBATCH -N 4
#SBATCH --ntasks-per-node=64
#SBATCH --error=ta205-err.%j
#SBATCH --mem=80GB
#SBATCH --time=00:30:00
#SBATCH -A cin_staff
#SBATCH -p knl_usr_prod
start_time
=
$(
date
+
"%s"
)
module purge
module load profile/knl
module load autoload qe/6.3_knl
export
OMP_NUM_THREADS
=
1
source
$INTEL_HOME
/performance_snapshots/apsvars.sh
srun
--cpu-bind
=
cores aps pw.x
-npool
2
-ndiag
32
-input
pw.in
end_time
=
$(
date
+
"%s"
)
walltime
=
$((
$end_time
-
$start_time
))
echo
"walltime
$walltime
"
quantum_espresso/README.md
View file @
6abed49d
...
...
@@ -189,7 +189,7 @@ An example SLURM batch script for the A2 partition is given below:
```
shell
#!/bin/bash
#SBATCH -N2
#SBATCH --tasks-per-node=
3
4
#SBATCH --tasks-per-node=
6
4
#SBATCH -A <accountno>
#SBATCH -t 1:00:00
...
...
@@ -199,18 +199,17 @@ module load profile/knl
module load autoload qe/6.0_knl
export
OMP_NUM_THREADS
=
4
export
OMP_NUM_THREADS
=
1
export
MKL_NUM_THREADS
=
${
OMP_NUM_THREADS
}
mpi
run pw.x
-npool
4
-input
file.in
>
file.out
s
run pw.x
-npool
2
-ndiag
16
-input
file.in
>
file.out
```
In the above with the SLURM directives we have asked for 2 KNL nodes (each with 68 cores) in
cache/quadrant mode and 93 Gb main memory each. We are running QE in
hybrid mode using 34 MPI processes/node, each with 4 OpenMP
threads/process and distributing the k-points in 4 pools; the Intel
MKl library will also use 4 OpenMP threads/process.
cache/quadrant mode and 93 Gb main memory each. We are running QE in MPI-only
mode using 64 MPI processes/node with the k-points in 2 pools; the diagonalisation of the Hamiltonian
will be done by 16 (4x4) tasks.
Note that this script needs to be submitted using the KNL scheduler as follows:
...
...
@@ -233,4 +232,4 @@ Please check the Cineca documentation for information on using the
| Large test case | CNT | Carbon nanotube | | Large scaling runs only. Memory and time requirements high|
Last updated: 14-January-2019
__
Last updated: 14-January-2019
__
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