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(updated: August 2019 )

In this page:

Table of Contents

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Model: Lenovo NeXtScale
Architecture: Linux Infiniband Cluster 
Nodes: 1022
Processors: 2 x 18-cores Intel Xeon E5-2697 v4 (Broadwell) at 2.30 GHz
Cores: 36 cores/node
RAM: 128 GB/node, 3.5 GB/core
Internal Network: Intel OmniPath, 100 Gb/s
Peak performance single node: 1.3 TFlop/s
Peak Performance: 1.5 PFlop/s
+

Accelerators: 60 nodes equipped with 1 nVidia K80 GPU
2 nodes equipped with 1 nVidia V100 GPU


Starting from 15th March 2021 Galileo will be turned off to make space for the new more performant infrastructure Galileo100.

The GALILEO supercomputer has been introduced first in January 2015 and in its first configuration, it has been available to the Italian public and industrial researchers until January 2018. It has been the national Tier-1 system for scientific research.

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Disks and Filesystems

The storage organisation conforms to the CINECA infrastructure (see Section "Data storage and Filesystems") . In addition to the home directory ($HOME), for each user is defined a scratch area $CINECA_SCRATCH, a large disk for storing run time data and files. $WORK is defined for each active project on the system, reserved for all the collaborators of the project. This is a safe storage area to keep run time data for the whole life of the project.


Total Dimension (TB)Quota (GB)Notes
$HOME20050
  • permanent/backed up, user specific, local
$CINECA_SCRATCH300no quota
  • temporary, user specific, local
  • automatic cleaning procedure of data older than 50 days (time interval can be reduced in case of critical usage ratio of the area. In this case, users will be notified via HPC-News)
$WORK3001.000
  • permanent, project specific, local
  • extensions can be considered if needed (mailto: superc@cineca.it)

It is also available a temporary storage local on compute nodes generated when the job starts and accessible via environment variable $TMPDIR. For more details please see the dedicated section of UG2.5: Data storage and FileSystems. On Galileo the $TMPDIR local area has 49 GB of available space.

$DRES points to the shared repository where Data RESources are maintained. This is a data archive area available only on-request, shared with all CINECA HPC systems and among different projects.

$DRES is not mounted on the compute nodes. This means that you can't access it within a batch job: all data needed during the batch execution has to be moved on $WORK or $CINECA_SCRATCH before the run starts.

Since all the filesystems are based on gpfs (General Parallel FIle System), the usual unix command "quota" is not working. Use the local command "cindata" to query for disk usage and quota ("cindata -h" for help):

  > cindata

Modules environment

The software modules are collected in different profiles and organized by functional category (compilers, libraries, tools, applications,..).

On GALILEO the profiles are of two types, “domain” type (chem, phys, lifesc,..) for the production activity and “programming” type (base and advanced) for compilation, debugging and profiling activities and that they can be loaded together.

"Base" profile is the default. It is automatically loaded after login and it contains basic modules for the programming activities (intel e gnu compilers, math libraries, profiling and debugging tools,..).

If you want to use a module placed under other profiles, for example an application module, you will have to load preventively the corresponding profile:

>module load profile/<profile name>
>module load autoload <module name>

For listing all profiles you have loaded you can use the following command:

>module list

In order to detect all profiles, categories and modules available on GALILEO the command “modmap” is available:

>modmap

With modmap you can see if the desired module is available and which profile you have to load to use it.

>modmap -m <module name>


Production environment

Since GALILEO 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 and Tools".

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:

> srun -N 1 --ntasks-per-node=2 -A <account_name> --pty /bin/bash

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

or

> mpirun ./myprogram
The default SLURM MPI type has been set equal to PMI2.

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.

Batch

As usual, 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 gll_all_serial partition is available with one core and a maximum walltime of 4 hours. It runs on two nodes and it is designed for pre/post-processing serial analysis, and for moving your data (via rsync, scp etc.) in case more than 10 minutes are required to complete the data transfer. In order to use this partition you have to specify the SLURM flag "-p":

#SBATCH -p gll_all_serial

The gll_all_serial partition has a limit of 1 task per job and 4GB of memory per job. If you wish to ask for more than a core on a single job, remember to add on your jobscript the specific about the memory limit, since the default per core is 3.5GB and therefore your job won't enter because the required memory exceeds the partition limit.


IMPORTANT FOR USERS OF THE PRE-UPGRADED VERSION OF GALILEO:  the old filesystems (such as $CINECA_SCRATCH) haven't been migrated to the upgraded cluster, but will remain available for a certain period of time (until the end of 2019) and visible only on specific nodes. You can access such nodes for transferring your data from the old environment to the new, by using the partition:

#SBATCH -p gll_all_transfer 

with the limitations of one core and 24 hours per job. Inside the gll_all_transfer nodes, you will find your old scratch area at the mount point /gpfs/scratch_old .


Graphic session

If a graphic session is desired we recommend to use the tool "RCM". See the corresponding session to know more about how to download and use RCM.

A complete reconfiguration of the RCM environment is in progress. This guide will be completed as soon as a final configuration will be implemented.


Submitting parallel Batch jobs

To run parallel batch jobs on GALILEO you need to specify the partition gll_usr_prod, or any other partition described in this user guide.

Users who need to run on GPU-equipped nodes need to specify the partition gll_usr_gpuprod.

If you do not specify the partition, your jobs will try to run on the default partition bdw_all_serial, meant for serial jobs, eventually failing if specific partition limits (maximum four tasks per job and maximum walltime of 4 hours) are violated.

The minimum number of cores you can request for a batch job is 1. The maximum number of cores that you can request is 2304 (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 36 will be assumed.

  • If you do not specify the amount of memory (as the value of the "SBATCH --mem" DIRECTIVE), a default value of 3000MB will be assumed.

  • The maximum memory per node is 118000MB

 

A special QOS (qos_special) is also available for not-ordinary types of jobs, such as a walltime larger than 24 hours. Since it violates our standard policy, there are restrictions in its usage, and users who want to use it need to be enabled by the User Support staff. Please write to superc@cineca.it in case you think you need to use it. Your request will be evaluated and, if approved, you will be allowed to use the special QOS for a limited period of time.


Use of GPUs on GALILEO

The gll_usr_gpuprod partition is defined on 42 Broadwell nodes (18-cores Intel Xeon E5-2697 v4 @ 2.40GHz), each equipped with 1 nVidia K80 GPUs (seen as two K40 gpus). All users using an account with available budget can submit jobs on this partition and use GPU nodes on GALILEO.  

The maximum number of nodes that can be required on gll_usr_gpuprod is 4 for a maximum walltime of 08:00:00 hours. The maximum memory is 118000 MB

In regards of writing a SLURM jobscript, you need to request the GPU as "gres":


#SBATCH --partition=gll_usr_gpuprod
#SBATCH --gres=gpu:kepler:N     (N=1,2)


GALILEO is also equipped with two nodes with one nVIDIA Volta (V100) GPUs each, accessible for tests for a limited period of time. Please write to superc@cineca.it if you are interested to test the Volta GPUs, with a brief motivation for your request. Once your request is approved and you are enabled to use these resources (via the association to a special QOS "gll_qos_gpudev"), you can submit jobs to the Volta node with the following options:


#SBATCH --partition=gll_usr_gpudev
#SBATCH --qos=gll_qos_gpudev
#SBATCH --gres=gpu:volta:1

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.

Using the specific QOS (i.e. specifying the QOS in the submission script) , and specifying the partition gll_spc_prod, users associated to the allowed project will run their jobs on reserved nodes in the gll_spc_prod partition:

>#SBATCH --partition=gll_spc_prod
>#SBATCH --qos=<specific_qos>


Summary

In the following table, you can find all the main features and limits imposed on the SLURM partitions and QOS.

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

gll_all_serial

(default partition)

noQOS

1

04:00:00

4 jobs / 4 cpus

 3000 (per core)

40

gll_all_transfer


noQOS1

24:00:00

/3000 (per core)40Temporary partition for accessing the filesystem related to the old version of GALILEO (UNTIL 29/02/2020)








gll_usr_prod

noQOS


gll_qos_dbg


gll_qos_bprod

min = 1

max = 2304 (64 nodes)

min = 1

max = 144

min = 65 nodes

max = 128 nodes

24:00:00


02:00:00


24:00:00

20 jobs


144 cpus/4nodes


128 nodes per account

256 nodes in total per qos

118000


118000


118000

40


95


85



higher priority than default qos

--qos=gll_qos_dbg


--qos=gll_qos_bprod

gll_usr_gpuprod

noQOS


min = 1

max = 144

08:00:00

4 nodes

118000

40

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

gll_spc_prod

Every account needs to have a valid QOS to access this partition

Depending on the QOS used by the particular account

Depending on the QOS used by the particular account

/

118000

40

Partition dedicated to specific kind of users.

gll_meteo_prod







Partition reserved to meteo services, NOT opened to production

 

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There are limitations to running parallel programs in the login shell. You should use the "Interactive SLURM" mode, as described in the "Interactive" section, previously on this page.Outgoing links:


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