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Production environment

Since GALILEO100 is a general purpose system and it is used by several users at the same time, long production jobs must be submitted using a queuing system. This guarantees that access to the resources is as fair as possible.

Roughly speaking, there are two different modes to use an HPC system: Interactive and Batch. For a general discussion see the section "Production Environment".

Interactive

serial program can be executed in the standard UNIX way:

> ./program

This is allowed only for very short runs, since the interactive environment set on the login nodes has a 10 minutes time limit: for longer runs please use the "batch" mode.

A parallel program can be executed interactively only by submitting an "Interactive" SLURM batch job, using the "srun" command: the job is queued and scheduled as any other job, but when executed, the standard input, output, and error streams are connected to the terminal session from which srun was launched.

For example, to start an interactive session with the MPI program "myprogram", using one node and two processors, you can launch the command:

> salloc -N 1 --ntasks-per-node=2 -A <account_name> 

SLURM will then schedule your job to start, and your shell will be unresponsive until free resources are allocated for you. If not specified, the default time limit for this kind of jobs is one hour.

When the shell returns a prompt inside the compute node, you can execute your program by typing:

> srun ./myprogram

(srun is recommended with respect to mpirun for this environment)


SLURM automatically exports the environment variables you defined in the source shell, so that if you need to run your program "myprogram" in a controlled environment (i.e. with specific library paths or options), you can prepare the environment in the login shell and be sure to find it again in the interactive shell o the compute node.

On systems using SLURM, you can submit a script script.x using the command:

> sbatch script.x

You can get a list of defined partitions with the command:
> sinfo

For more information and examples of job scripts, see section Batch Scheduler SLURM.

Submitting serial Batch Jobs

The partition will be available in the full production.


Graphic session

If a graphic session is desired we recommend to use the tool "RCM". Please install the latest version of RCM. See the corresponding paragraph to know more about how to download and use RCM.

Submitting parallel Batch Jobs

To run parallel batch jobs on GALILEO100 you need to specify the partition and the qos that are described in this user guide.

If you do not specify the partition, your jobs will try to run on the default partition g100_all_serial.

The minimum number of cores you can request for a batch job is 1. The maximum number of cores that you can request is 3072 (64 nodes). It is also possible to request a maximum walltime of 24 hours. Defaults are as follows:

  • If you do not specify the walltime (by means of the #SBATCH --time directive), a default value of 30 minutes will be assumed.

  • If you do not specify the number of cores (by means of the "SBATCH -n" directive) a default value of 1 core will be assumed.

  • If you do not specify the amount of memory (as the value of the "SBATCH --mem" DIRECTIVE), a default value of 7800 MB per core will be assumed on g100_usr_prod and g100_usr_smem partitions. While on the g100_usr_bmem partition, the default value of memory assumed is  63200 MB per core.

The maximum memory per node is 375300MB (366.5GB) for thin and viz nodes, about 3TB for fat nodes. A study on the performances of the thin and fat nodes is ongoing.

On GALILEO100 there are four partitions dedicated to the production:

  • g100_usr_prod: this partition collects all the thin and persistent memory nodes (memory per node 375300 MB).
  • g100_usr_smem: this partition is composed only of thin nodes (memory per node 375300 MB).
  • g100_usr_pmem: this partition is composed only of Persistent memory nodes - more info in a following update (memory per node 375300 MB).
  • g100_usr_bmem: this partition is composed only of fat nodes (memory per node 3 TB). It is reserved for jobs that need more than 375300 MB of memory per node and is out of the g100_usr_prod partition.

We encourage you to use the partition more suitable for your job. For more information on the partitions look to Summary.


Processor affinity

Processor affinity, or CPU pinning, enables the binding of processes and threads to a CPU (or group of CPUs). It is crucial to ensure the correct affinity so to avoid the CPUs overallocation, with a significant reduction of performances. It becomes a critical matter when you ask for a full node but, for your specific reasons (memory needs etc.) you don't use all the cores.  

The following indications work when running your executables with srun, which is the recommended option against mpirun. We refer to a hybrid MPI/OpenMP case compiled with the Intel oneAPI suite.

Given your optimal value of OMP_NUM_THREADS and number of processes, to obtain the full node ask for a number of task such that  ( --ntasks-per-node * --cpus-per-task )= 48.

  • To avoid the processes over allocation of cores rely on the --cpu-bind=cores option of srun  (you can skip it if you use all the requested cores)
  • To enforce the threads affinity use the Intel parameter KMP_AFFINITY, or the OpenMP parameter OMP_PLACES
  • To distribute the MPI tasks consecutively inside the sockets, use the -m block:block option of srun (or the equivalent sbatch directive #SBATCH -m block:block)
#!/bin/bash
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=12
#SBATCH --cpus-per-task=4
#SBATCH --account=<your_account>
module load autoload intelmpi/oneapi-2021--binary
export OMP_NUM_THREADS=4
export KMP_AFFINITY=compact    # or OMP_PLACES=cores
srun --cpu-bind=cores -m block:block <your_exe>

Use of GPUs on Galileo100

to be soon defined

Users with reserved resources

Users of projects that require reserved resources (such as industrial users or users associated to an agreement that involves dedicated resources) will be associated to a QOS qos_ind.

Using the  qos_ind (i.e. specifying the QOS in the submission script) , and specifying the partition g100_spc_prod, users associated to the allowed project will run their jobs on reserved nodes in the g100_spc_prod partition with the features and limits imposed for the particular account.

>#SBATCH --partition=g100_spc_prod
>#SBATCH --qos=qos_ind


Summary

In the following table, you can find all the main features and limits imposed on the SLURM partitions and QOS. For all partitions, if the memory is not explicitly requested, a DefMemPerCPU = 7800 will be assigned for each requested core. If the walltime is not explicitly requested, a DefaultTime=00:30:00 will be assigned to the job. If the partition is not explicitly requested, the default g100_all_serial partition will be assigned.

SLURM

partition

QOS

# cores per job

max walltime

max running jobs per user/

max n. of cpus/nodes per user

max memory per node

(MB)

priority

notes

g100_all_serial
(DEFAULT)

noQOSmax = 4

04:00:00

4 jobs31,200 (30 GB)40

on two login nodes

budget-free

qos_installmax = 1604:00:00max =16 cores
1 job per user
100 GB40request to superc@cineca.it



g100_usr_prod

g100_usr_smem

g100_usr_pmem

noQOS

min = 1
max =  32 nodes

24:00:00






375,300 (366 GB)


40



runs on thin and persistent memory nodes

runs only on thin nodes

runs only on persistent memory nodes

g100_qos_dbg

min = 1
max = 96 (2 nodes)

02:00:00
80
g100_qos_bprod

min = 1537 (33 nodes)
max = 3072 (64 nodes)

24:00:00


60
g100_qos_lprod

min=1
max=2 nodes

4-00:00:00

max 2 nodes per user

40
qos_special> 32 nodes> 24:00:00
40request to superc@cineca.it

g100_usr_bmem


noQOS25 nodes

24:00:00


3,036,000  (3 TB)

40runs on fat nodes

g100_usr_interactive


noQOS2 nodes

8:00:00


375,300 (366 GB)

40on nodes with GPUs

--gres=gpu:N (N=1,2)

g100_spc_prod

qos_ind

Depending on the specific agreement

24:00:00


375,300 (366 GB)

n/a

Partition dedicated to specific kinds of users.

Runs on thin nodes

g100_meteo_prod

qos_meteo


24:00:00
375,300 (366 GB)
40

Partition reserved to meteo services, NOT opened to production

Runs on thin nodes

 

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