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150

Booster

DCGP

Model

Atos BullSequana X2135 "Da Vinci" single-node GPU blade

Atos BullSequana X2140 three-node CPU blade

Racks

116
22

Nodes

3456

1536

Processors

single socket 32 cores Intel Ice Lake Lake CPU

1 x Intel Xeon Platinum 8358 CPU, 2.60GHz60GHz  TDP 250W

dual socket 56 cores sockets Intel Sapphire Rapids CPU

2 x Intel CPU, TDB Xeon Platinum 8480p, 2.00 GHz TDP 350W

Accelerators

4 x NVIDIA Ampere GPUs/node, 64GB HBM2 HBM2e NVLink 3.0 (200GB/s) 

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Cores

32 cores/node

112 cores/node

RAM

512 (8x64) GB DDR4 3200 MHz

512 (16 x 32) GB DDR5 4800 MHz

Peak Performance

about 309 Pflop/s

9 Pflops/s


Internal Network

DragonFly+ 200 Gbps (NVIDIA Mellanox HDR DragonFly++ 200Gb/s
2 x NVIDIA HDR 2 x 100 Gb/s cards (Booster nodes)
3 x Nvidia HDR100 1 x 100 Gb/s cards (DCGP nodes)Infiniband HDR) 

2 x dual port HDR100 per node

 single port HDR100 per node

Storage
(raw capacity)

137.6 PB based on DDN ES7990X and Hard Drive Disks

Disk Space

106PB Large capacity storage, 620 GB/s (Capacity Tier)
5.4 PB of High performance storage, 1.4 TB/s 7 PB based on DDN ES400NVX2 and Solid State Drives (Fast Tier) 







Peak performance details

Node Performance

Theoretical
Peak
Performance

CPU (nominal/peak freq.)1680 Gflops
GPU75000 Gflops
Total76680 GFlops
Memory Bandwidth (nominal/peak freq.)24.4 GB/s

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The account_name (or project) is important for batch executions. You need to indicate an account_no name to be accounted for in the scheduler, using the flag "-A"

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With the "saldo -b" command you can list all the account_name associated with your username. 

$ saldo -b          (reports projects defined on LEONARDO Booster)
$ saldo --dcgp -b (reports projects defined on LEONARDO DCGP)

Please note that the accounting is in terms of consumed core hours, but it strongly depends also on the requested memory and local storage, and number of GPUs, please refer to the dedicated section.

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In addition to the home directory $HOME, for each user is defined a scratch area $SCRATCH (or $CINECA_SCRATCH), a large disk for the storage of run time data and files.
An new user specific area $PUBLIC is defined on LEONARDO, useful for example to share installations with other users (it is indeed the default directory for SPACK sub-directories, see more details in the dedicated page).
$WORK area is defined for each active project on the system, reserved to all the collaborators of the project. A corresponding $FAST area is defined for each active project on the scratch filesystem, on its subset of "fast" NVMe SSD flash drives. As for $WORK, the $FAST area is reserved to all the collaborators of the project. An extension of the default $WORK quota (1 TB) can be granted if justified and essential for the course of the project's activity, while the use of the $FAST is limited to 1 TB of space per project.  


Total Dimension (TB)

Quota (GB)

Notes

$HOME0.46 PiB50GB per user
  • permanent
  • backed up (suspended)
  • user specific
$CINECA_SCRATCH41.4 40 PiBno quota
  • HDD storage
  • temporary
  • user specific
  • no backup
  • automatic cleaning procedure of data older than 40 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).
$PUBLIC0.46 PiB50GB per user
  • permanent
  • user specific
  • no backup
$WORK10 30 PB

1TB per project

  • permanent
  • project specific
  • no backup
  • extensions can be considered if needed (mailto: superc@cineca.it)
$FAST3.5PB1TB per project
  • permanent
  • project specific
  • no backup
  • The automatic cleaning of the scratch area is NOT active yet, but it will soon be enforced.

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It is also available a temporary storage area local to nodes on login and compute nodes (on the latter it is generated when the job starts and removed when it ends) and accessible via environment variable $TMPDIR. This area is:

  • on the local SSD disks on login nodes (14 TB of capacity), mounted as /scratch_local (TMPDIR=/scratch_local). This is a shared area with no quota, remove all the files once they are not requested anymore. A cleaning procedure will be enforced in case of improper use of the area.   
  • on the local SSD disks on the serial node (lrd_all_serial, 14TB of capacity), managed via the slurm job_container/tmpfs plugin. This plugin provides a job-specific, private temporary file system space, with private instances of /tmp and /dev/shm in the job's user space (TMPDIR=/tmp, visible via the command "df -h"), removed at the end of the serial job. You can request the resource via sbatch directive or srun option "--gres=tmpfs:XX" (for instance: --gres=tmpfs:200G), with a maximum of 1 TB for the serial jobs. If not explicitly requested, the /tmp has the default dimension of 10 GB.
  • on the local SSD disks on DCGP nodes (3 TB  of capacity). Like with the serial node, the local /tmp and /dev/shm areas are managed via plugin, which at the start of the jobs mounts private instances of /tmp and /dev/shm in the job's user space (TMPDIR=/tmp, visible via the command "df -h /tmp"), and unmounts them at the end of the job (all data will be lost). You can request the resource via sbatch directive or srun option "--gres=tmpfs:XX", with a maximum of all the available 3 TB for DCGP nodes. Like with the serial node, if not explicitly requested, the /tmp has the default dimension of 10 GB. Please note: for the DCGP jobs the requested amount of gres/tmpfs resource contributes to the consumed budget, changing the number of accounted equivalent core hours, see the dedicated section on the Accounting
  • on RAM on the diskless booster nodes (with a fixed size of 10 GB, no increase is allowed, and the gres/tmpfs resource is disabled).

For a general discussion on the TMPDIR area, For more details please see the dedicated section of Data storage and FileSystems.

Since all the filesystems are based on Lustre, the usual unix command "quota" is not working. Use the local command cindata to query for disk usage and quota ("cindata -h" for help) that will be available soon.

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:

$ cindata

or the tool "cinQuota" available in the module cintools

$ cinQuota

For more details about both these commands, please consult the section dedicated to how to monitor the occupancy.

Software environment

Module environment

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Note: on LEONARDO you can find modules compiled to support GPUs and modules suitable only for CPUs. You can check the compiler in the full name of the module, where the version is specified (e.g. gromacs/2022.3--intel-oneapi-mpi--2021.10.0--oneapi–2023.2.0). Remind that modules compiled with gcc, nvhpc, cuda should be used only on the Booster partition, while modules compiled with intel oneapi are suitable for running on the DGCP partition. Please refer to the specific sections of the two partitons for more details on the available compilers: Booster Programming environment and DCGP Programming environment.Note also that since the DCGP partition is currently in the pre-production phase, changes in the Module environment may occur. Please read the UserGuide for updates.

 Spack environment

In case you don't find a software you are interested in, you can install it by yourself. 
In this case, on LEONARDO  we offer the possibility to use the “spack” environment by loading the corresponding module. Please refer to the dedicated section in UG2.6: Production Environment

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