Please confer /etc/slurm/README.
The documentation of Slurm can be found ?here.
Slurm offers interactive and batch jobs (scripts submitted into the system). The relevant commands are srun
and sbatch
. The srun
command can be used to spawn processes (please do not use mpiexec), both from the frontend and from within a batch script. You can also get a shell on a node to work locally there (e.g. to compile your application natively for a special platform.
By default, Slurm passes the environment from your job submission session directly to the execution environment. Please be aware of this when running jobs with srun
or when submitting scripts with sbatch
. This behavior can be controlled via the --export
option. Please refer to the ?Slurm documentation to get more information about this.
In particular, when submitting job scripts, it is recommended to load the necessary modules within the script and submit the script from a clean environment.
Suppose you have an mpi executable named hello_mpi
. There are three ways to start the binary.
First, start a shell on a node. You would like to run your mpi task on 4 machines with 2 tasks per machine:
niessen@deepl:src/mpi > srun --partition=sdv -N 4 -n 8 --pty /bin/bash -i niessen@deeper-sdv04:/direct/homec/zdvex/niessen/src/mpi >
The environment is transported to the remote shell, no .profile
, .bashrc
, … are sourced (especially not the modules default from /etc/profile.d/modules.sh
).
Once you get to the compute node, start your application using srun
. Note that the number of tasks used is the same as specified in the initial srun
command above (4 nodes with two tasks each):
niessen@deeper-sdv04:/direct/homec/zdvex/niessen/src/mpi > srun ./hello_cluster srun: cluster configuration lacks support for cpu binding Hello world from process 6 of 8 on deeper-sdv07 Hello world from process 7 of 8 on deeper-sdv07 Hello world from process 3 of 8 on deeper-sdv05 Hello world from process 4 of 8 on deeper-sdv06 Hello world from process 0 of 8 on deeper-sdv04 Hello world from process 2 of 8 on deeper-sdv05 Hello world from process 5 of 8 on deeper-sdv06 Hello world from process 1 of 8 on deeper-sdv04
You can ignore the warning about the cpu binding. ParaStation will pin you processes.
You can run the application directly from the frontend, bypassing the shell:
niessen@deepl:src/mpi > srun --partition=sdv -N 4 -n 8 ./hello_cluster Hello world from process 4 of 8 on deeper-sdv06 Hello world from process 6 of 8 on deeper-sdv07 Hello world from process 3 of 8 on deeper-sdv05 Hello world from process 0 of 8 on deeper-sdv04 Hello world from process 2 of 8 on deeper-sdv05 Hello world from process 5 of 8 on deeper-sdv06 Hello world from process 7 of 8 on deeper-sdv07 Hello world from process 1 of 8 on deeper-sdv04
In this case, it can be useful to create an allocation which you can use for several runs of your job:
niessen@deepl:src/mpi > salloc --partition=sdv -N 4 -n 8 salloc: Granted job allocation 955 niessen@deepl:~/src/mpi>srun ./hello_cluster Hello world from process 3 of 8 on deeper-sdv05 Hello world from process 1 of 8 on deeper-sdv04 Hello world from process 7 of 8 on deeper-sdv07 Hello world from process 5 of 8 on deeper-sdv06 Hello world from process 2 of 8 on deeper-sdv05 Hello world from process 0 of 8 on deeper-sdv04 Hello world from process 6 of 8 on deeper-sdv07 Hello world from process 4 of 8 on deeper-sdv06 niessen@deepl:~/src/mpi> # several more runs ... niessen@deepl:~/src/mpi>exit exit salloc: Relinquishing job allocation 955
Given the following script hello_cluster.sh
: (it has to be executable):
#!/bin/bash #SBATCH --partition=sdv #SBATCH -N 4 #SBATCH -n 8 #SBATCH -o /homec/zdvex/niessen/src/mpi/hello_cluster-%j.log #SBATCH -e /homec/zdvex/niessen/src/mpi/hello_cluster-%j.err #SBATCH --time=00:10:00 srun ./hello_cluster
This script requests 4 nodes with 8 tasks, specifies the stdout and stderr files, and asks for 10 minutes of walltime. Submit:
niessen@deepl:src/mpi > sbatch ./hello_cluster.sh Submitted batch job 956
Check what it's doing:
niessen@deepl:src/mpi > squeue JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON) 956 sdv hello_cl niessen R 0:00 4 deeper-sdv[04-07]
Check the result:
niessen@deepl:src/mpi > cat hello_cluster-956.log Hello world from process 5 of 8 on deeper-sdv06 Hello world from process 1 of 8 on deeper-sdv04 Hello world from process 7 of 8 on deeper-sdv07 Hello world from process 3 of 8 on deeper-sdv05 Hello world from process 0 of 8 on deeper-sdv04 Hello world from process 2 of 8 on deeper-sdv05 Hello world from process 4 of 8 on deeper-sdv06 Hello world from process 6 of 8 on deeper-sdv07
As of version 17.11 of Slurm, heterogeneous jobs are supported. For example, the user can run:
srun --partition=dp-cn -N 1 -n 1 hostname : --partition=dp-dam -N 1 -n 1 hostname dp-cn01 dp-dam01
Please notice the :
separating the definitions for each sub-job of the heterogeneous job. Also, please be aware that it is possible to have more than two sub-jobs in a heterogeneous job.
The user can also request several sets of nodes in a heterogeneous allocation using salloc
. For example:
salloc --partiton=dp-cn -N 2 : --partition=dp-dam -N 4
In order to submit a heterogeneous job via sbatch
, the user needs to set the batch script similar to the following one:
#!/bin/bash #SBATCH --job-name=imb_execute_1 #SBATCH --account=deep #SBATCH --mail-user= #SBATCH --mail-type=ALL #SBATCH --output=job.out #SBATCH --error=job.err #SBATCH --time=00:02:00 #SBATCH --partition=dp-cn #SBATCH --nodes=1 #SBATCH --ntasks=12 #SBATCH --ntasks-per-node=12 #SBATCH --cpus-per-task=1 #SBATCH packjob #SBATCH --partition=dp-dam #SBATCH --constraint= #SBATCH --nodes=1 #SBATCH --ntasks=12 #SBATCH --ntasks-per-node=12 #SBATCH --cpus-per-task=1 srun ./app_cn : ./app_dam
Here the packjob
keyword allows to define Slurm parameter for each sub-job of the heterogeneous job. Some Slurm options can be defined once at the beginning of the script and are automatically propagated to all sub-jobs of the heterogeneous job, while some others (i.e. --nodes
or --ntasks
) must be defined for each sub-job. You can find a list of the propagated options on the ?Slurm documentation.
When submitting a heterogeneous job with this colon notation using ParaStationMPI, a unique MPI_COMM_WORLD
is created, spanning across the two partitions. If this is not desired, one can use the --pack-group
key to submit independent job steps to the different node-groups of a heterogeneous allocation:
srun --pack-group=0 ./app_cn ; srun --pack-group=1 ./app_dam
Using this configuration implies that inter-communication must be established manually by the applications during run time, if needed.
For more information about heterogeneous jobs please refer to the ?relevant page of the Slurm documentation.
In order to establish MPI communication across modules using different interconnect technologies, some special Gateway nodes must be used. On the DEEP-EST system, MPI communication across gateways is needed only between Infiniband and Extoll interconnects.
Attention: During the first part of 2020, only the DAM nodes will have Extoll interconnect, while the CM and the ESB nodes will be connected via Infiniband. This will change later during the course of the project (expected Summer 2020), when the ESB will be equipped with Extoll connectivity (Infiniband, which will be removed from the ESB and left only for the CM).
A general description of how the user can request and use gateway nodes is provided at ?this section of the JURECA documentation.
Attention: some information provided on the JURECA documentation do not apply for the DEEP system. In particular:
xenv
utility (necessary on JURECA to load modules for different architectures - Haswell and KNL) is needed on DEEP only to load the extoll
module on the DAM and ESB nodes (the extoll
module is not available on the CM. Trying to load it there will produce an error and cause the job to fail). All the other modules can be loaded via the usual module load
or ml
command on the batch script before the srun
command. If desired, xenv
can still be used to load different set of modules for different sub-jobs of a heterogeneous jobs.
Please note that there is no default partition configured. In order to run a job, you have to specify one of the following partitions, using the --partition=...
switch:
Anytime, you can list the state of the partitions with the sinfo
command. The properties of a partition can be seen using
scontrol show partition <partition>
The sacct
command can be used to enquire the Slurm database about a past job.
Yes, it is available ?here.
You can check the state of your job with
scontrol show job <job id>
In the output, look for the Reason
field.
You can check the existing reservations using
scontrol show res
Please use the squeue
command.
Please confer the sbatch
/srun
man page, especially the
-d, --dependency=<dependency_list>
entry.
Also, jobs chan be chained after they have been submitted using the scontrol
command by updating their Dependency
field.
The main command to use is sinfo
. By default, when called alone, sinfo
will list the available partitions and the number of nodes in each partition in a given status. For example:
[deamicis1@deepv hybridhello]$ sinfo PARTITION AVAIL TIMELIMIT NODES STATE NODELIST sdv up 20:00:00 16 idle deeper-sdv[01-16] knl up 20:00:00 1 drain knl01 knl up 20:00:00 3 idle knl[04-06] knl256 up 20:00:00 1 drain knl01 knl256 up 20:00:00 1 idle knl05 knl272 up 20:00:00 2 idle knl[04,06] snc4 up 20:00:00 1 idle knl05 dam up 20:00:00 1 down* protodam01 dam up 20:00:00 3 idle protodam[02-04] extoll up 20:00:00 16 idle deeper-sdv[01-16] ml-gpu up 20:00:00 1 idle ml-gpu01 dp-cn up 20:00:00 1 drain dp-cn49 dp-cn up 20:00:00 2 alloc dp-cn[01,50] dp-cn up 20:00:00 47 idle dp-cn[02-48] dp-dam up 20:00:00 1 drain* dp-dam01 dp-dam up 20:00:00 1 drain dp-dam02 dp-dam up 20:00:00 14 down dp-dam[03-16] dp-sdv-esb up 20:00:00 2 idle dp-sdv-esb[01-02] psgw-cluster up 20:00:00 1 down* nfgw01 psgw-booster up 20:00:00 1 down* nfgw02 debug up 20:00:00 1 drain* dp-dam01 debug up 20:00:00 1 down* protodam01 debug up 20:00:00 3 drain dp-cn49,dp-dam02,knl01 debug up 20:00:00 14 down dp-dam[03-16] debug up 20:00:00 2 alloc dp-cn[01,50] debug up 20:00:00 69 idle deeper-sdv[01-16],dp-cn[02-48],knl[04-06],protodam[02-04]
Please refer to the man page for sinfo
for more information.
-joe
in Torque?Not directly. In your batch script, redirect stdout and stderr to the same file:
...
#SBATCH -o /point/to/the/common/logfile-%j.log
#SBATCH -e /point/to/the/common/logfile-%j.log
...
(The %j
will place the job id in the output file). N.B. It might be more efficient to redirect the output of your script's commands to a dedicated file.
DEEP uses a ParTec-modified version of Slurm called psslurm. In psslurm, the options concerning binding and pinning are different from the ones provided in Vanilla Slurm. By default, psslurm will use a by rank pinning strategy, assigning each Slurm task to a different physical thread on the node starting from OS processor 0. For example:
[deamicis1@deepv hybridhello]$ OMP_NUM_THREADS=1 srun -N 1 -n 4 -p dp-cn ./HybridHello | sort -k9n -k11n Hello from node dp-cn50, core 0; AKA rank 0, thread 0 Hello from node dp-cn50, core 1; AKA rank 1, thread 0 Hello from node dp-cn50, core 2; AKA rank 2, thread 0 Hello from node dp-cn50, core 3; AKA rank 3, thread 0
Attention: please be aware that the psslurm affinity settings only affect the tasks spawned by Slurm. When using threaded applications, the thread affinity will be inherited from the task affinity of the process originally spawned by Slurm. For example, for a hybrid MPI-OpenMP application:
[deamicis1@deepv hybridhello]$ OMP_NUM_THREADS=4 srun -N 1 -n 4 -c 4 -p dp-dam ./HybridHello | sort -k9n -k11n Hello from node dp-dam01, core 0-3; AKA rank 0, thread 0 Hello from node dp-dam01, core 0-3; AKA rank 0, thread 1 Hello from node dp-dam01, core 0-3; AKA rank 0, thread 2 Hello from node dp-dam01, core 0-3; AKA rank 0, thread 3 Hello from node dp-dam01, core 4-7; AKA rank 1, thread 0 Hello from node dp-dam01, core 4-7; AKA rank 1, thread 1 Hello from node dp-dam01, core 4-7; AKA rank 1, thread 2 Hello from node dp-dam01, core 4-7; AKA rank 1, thread 3 Hello from node dp-dam01, core 8-11; AKA rank 2, thread 0 Hello from node dp-dam01, core 8-11; AKA rank 2, thread 1 Hello from node dp-dam01, core 8-11; AKA rank 2, thread 2 Hello from node dp-dam01, core 8-11; AKA rank 2, thread 3 Hello from node dp-dam01, core 12-15; AKA rank 3, thread 0 Hello from node dp-dam01, core 12-15; AKA rank 3, thread 1 Hello from node dp-dam01, core 12-15; AKA rank 3, thread 2 Hello from node dp-dam01, core 12-15; AKA rank 3, thread 3
Be sure to explicitly set the thread affinity settings in your script (e.g. exporting environment variables) or directly in your code. Taking the previous example:
[deamicis1@deepv hybridhello]$ OMP_NUM_THREADS=4 OMP_PROC_BIND=close srun -N 1 -n 4 -c 4 -p dp-dam ./HybridHello | sort -k9n -k11n Hello from node dp-dam01, core 0; AKA rank 0, thread 0 Hello from node dp-dam01, core 1; AKA rank 0, thread 1 Hello from node dp-dam01, core 2; AKA rank 0, thread 2 Hello from node dp-dam01, core 3; AKA rank 0, thread 3 Hello from node dp-dam01, core 4; AKA rank 1, thread 0 Hello from node dp-dam01, core 5; AKA rank 1, thread 1 Hello from node dp-dam01, core 6; AKA rank 1, thread 2 Hello from node dp-dam01, core 7; AKA rank 1, thread 3 Hello from node dp-dam01, core 8; AKA rank 2, thread 0 Hello from node dp-dam01, core 9; AKA rank 2, thread 1 Hello from node dp-dam01, core 10; AKA rank 2, thread 2 Hello from node dp-dam01, core 11; AKA rank 2, thread 3 Hello from node dp-dam01, core 12; AKA rank 3, thread 0 Hello from node dp-dam01, core 13; AKA rank 3, thread 1 Hello from node dp-dam01, core 14; AKA rank 3, thread 2 Hello from node dp-dam01, core 15; AKA rank 3, thread 3
Please refer to the ?following page on the JURECA documentation for more information about how to affect affinity on the DEEP system using psslurm options. Please be aware that different partitions on DEEP have different number of sockets per node and cores/threads per socket with respect to JURECA. Please refer to the System_overview or run the lstopo-no-graphics
on the compute nodes to get more information about the hardware configuration on the different modules.
On DEEP, SMT is enabled by default on all nodes. Please be aware that on all JSC systems (including DEEP), each hardware thread is exposed by the OS as a separate CPU. For a n-core node, with m hardware threads per core, the OS cores from 0 to n-1 will correspond to the first hardware thread of all hardware cores (from all sockets), the OS cores from n to 2n-1 to the second hardware thread of the hardware cores, and so on.
For instance, on a Cluster node (with two sockets with 12 cores each, with 2 hardware threads per core):
[deamicis1@deepv hybridhello]$ srun -N 1 -n 1 -p dp-cn lstopo-no-graphics --no-caches --no-io --no-bridges --of ascii ?????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????? ? Machine (191GB total) ? ? ? ? ?????????????????????????????????????????????????????????????????????????? ?????????????????????????????????????????????????????????????????????????? ? ? ? ?????????????????????????????????????????????????????????????????????? ? ? ?????????????????????????????????????????????????????????????????????? ? ? ? ? ? NUMANode P#0 (95GB) ? ? ? ? NUMANode P#1 (96GB) ? ? ? ? ? ?????????????????????????????????????????????????????????????????????? ? ? ?????????????????????????????????????????????????????????????????????? ? ? ? ? ? ? ? ? ? ? ?????????????????????????????????????????????????????????????????????? ? ? ?????????????????????????????????????????????????????????????????????? ? ? ? ? ? Package P#0 ? ? ? ? Package P#1 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ??????????????? ??????????????? ??????????????? ??????????????? ? ? ? ? ??????????????? ??????????????? ??????????????? ??????????????? ? ? ? ? ? ? ? Core P#0 ? ? Core P#1 ? ? Core P#2 ? ? Core P#3 ? ? ? ? ? ? Core P#0 ? ? Core P#3 ? ? Core P#4 ? ? Core P#8 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ? ? ? PU P#0 ? ? ? ? PU P#1 ? ? ? ? PU P#2 ? ? ? ? PU P#3 ? ? ? ? ? ? ? ? PU P#12 ? ? ? ? PU P#13 ? ? ? ? PU P#14 ? ? ? ? PU P#15 ? ? ? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ? ? ? PU P#24 ? ? ? ? PU P#25 ? ? ? ? PU P#26 ? ? ? ? PU P#27 ? ? ? ? ? ? ? ? PU P#36 ? ? ? ? PU P#37 ? ? ? ? PU P#38 ? ? ? ? PU P#39 ? ? ? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ? ??????????????? ??????????????? ??????????????? ??????????????? ? ? ? ? ??????????????? ??????????????? ??????????????? ??????????????? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ??????????????? ??????????????? ??????????????? ??????????????? ? ? ? ? ??????????????? ??????????????? ??????????????? ??????????????? ? ? ? ? ? ? ? Core P#4 ? ? Core P#9 ? ? Core P#10 ? ? Core P#16 ? ? ? ? ? ? Core P#9 ? ? Core P#10 ? ? Core P#11 ? ? Core P#16 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ? ? ? PU P#4 ? ? ? ? PU P#5 ? ? ? ? PU P#6 ? ? ? ? PU P#7 ? ? ? ? ? ? ? ? PU P#16 ? ? ? ? PU P#17 ? ? ? ? PU P#18 ? ? ? ? PU P#19 ? ? ? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ? ? ? PU P#28 ? ? ? ? PU P#29 ? ? ? ? PU P#30 ? ? ? ? PU P#31 ? ? ? ? ? ? ? ? PU P#40 ? ? ? ? PU P#41 ? ? ? ? PU P#42 ? ? ? ? PU P#43 ? ? ? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ? ??????????????? ??????????????? ??????????????? ??????????????? ? ? ? ? ??????????????? ??????????????? ??????????????? ??????????????? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ??????????????? ??????????????? ??????????????? ??????????????? ? ? ? ? ??????????????? ??????????????? ??????????????? ??????????????? ? ? ? ? ? ? ? Core P#18 ? ? Core P#19 ? ? Core P#25 ? ? Core P#26 ? ? ? ? ? ? Core P#17 ? ? Core P#18 ? ? Core P#24 ? ? Core P#26 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ? ? ? PU P#8 ? ? ? ? PU P#9 ? ? ? ? PU P#10 ? ? ? ? PU P#11 ? ? ? ? ? ? ? ? PU P#20 ? ? ? ? PU P#21 ? ? ? ? PU P#22 ? ? ? ? PU P#23 ? ? ? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ? ? ? PU P#32 ? ? ? ? PU P#33 ? ? ? ? PU P#34 ? ? ? ? PU P#35 ? ? ? ? ? ? ? ? PU P#44 ? ? ? ? PU P#45 ? ? ? ? PU P#46 ? ? ? ? PU P#47 ? ? ? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ??????????? ? ? ? ? ? ? ? ??????????????? ??????????????? ??????????????? ??????????????? ? ? ? ? ??????????????? ??????????????? ??????????????? ??????????????? ? ? ? ? ? ?????????????????????????????????????????????????????????????????????? ? ? ?????????????????????????????????????????????????????????????????????? ? ? ? ?????????????????????????????????????????????????????????????????????????? ?????????????????????????????????????????????????????????????????????????? ? ?????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????? ?????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????? ? Host: dp-cn50 ? ? ? ? Indexes: physical ? ? ? ? Date: Thu 21 Nov 2019 15:22:31 CET ? ??????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????
The PU P#X
are the Processing Units numbers exposed by the OS.
To exploit SMT, simply run a job using a number of tasks*threads_per_task higher than the number of physical cores available on a node. Please refer to the ?relevant page of the JURECA documentation for more information on how to use SMT on the DEEP nodes.
Attention: currently the only way of assign Slurm tasks to hardware threads belonging to the same hardware core is to use the --cpu-bind
option of psslurm using mask_cpu
to provide affinity masks for each task. For example:
[deamicis1@deepv hybridhello]$ OMP_NUM_THREADS=2 OMP_PROC_BIND=close OMP_PLACES=threads srun -N 1 -n 2 -p dp-dam --cpu-bind=mask_cpu:$(printf '%x' "$((2#1000000000000000000000000000000000000000000000001))"),$(printf '%x' "$((2#10000000000000000000000000000000000000000000000010))") ./HybridHello | sort -k9n -k11n Hello from node dp-dam01, core 0; AKA rank 0, thread 0 Hello from node dp-dam01, core 48; AKA rank 0, thread 1 Hello from node dp-dam01, core 1; AKA rank 1, thread 0 Hello from node dp-dam01, core 49; AKA rank 1, thread 1
This can be cumbersome for jobs using a large number of tasks per node. In such cases, a tool like ?hwloc (currently available on the compute nodes, but not on the login node!) can be used to calculate the affinity masks to be passed to psslurm.