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Sections Production environment, Programming environment are specific for the two partitions, Booster and Data Centric General Purpose (DCGP):
- LEONARDO Booster UserGuide
- LEONARDO Data Centric DCGP UserGuide
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hostname: login.leonardo.cineca.it
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early availability: March, 2023 (Booster)
start of pre-production:June, 2023 (Booster)
January 2024 (Data CentricDCGP)
start of production: August 2023 (Booster)
February 2024 (DCGP)
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This HPC system is the new pre-exascale Tier-0 EuroHPC Joint Undertaking supercomputer hosted by CINECA and currently built in the Bologna Technopole, Italy. It is supplied by EVIDEN ATOS, and it is based on two new specifically-designed compute blades, which are available through two distinct SLURM partitions on the cluster:
- X2135 GPU blade based on NVIDIA Ampere A100-64 accelerators - LEONARDO Booster partition
- X2140 CPU-only blade based on Intel Sapphire Rapids processors - LEONARDO Data Centric General Purpose (DCGP) partition
The overall system architecture also uses NVIDIA Mellanox InfiniBand High Data Rate (HDR) connectivity, with smart in-network computing acceleration engines that enable extremely low latency and high data throughput to provide the highest AI and HPC application performance and scalability.
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The Operating System is RedHat Enterprise Linux 8.6.
System Architecture
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Internal Network: Nvidia Mellanox HDR DragonFly+ 200 Gb/s
Storage: 106 PB (raw) Large capacity storage, 620 GB/s
High Performance Storage 5.4 PB, 1.4 TB/s Based on 31 x DDN Exascaler ES400NVX2Login nodes: 4 nodes, icelake no-gpu
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Peak performance details
| Node Performance | ||
Theoretical | CPU (nominal/peak freq.) | 1680 Gflops |
| GPU | 75000 Gflops | |
| Total | 76680 GFlops | |
| Memory Bandwidth (nominal/peak freq.) | 24.4 GB/s | |
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which establishes a connection to one of the available login nodes. To connect to Leonardo LEONARDO you can also indicate explicitly the login nodes:
$ login01-ext.leonardo.cineca.it
$ login02-ext.leonardo.cineca.it
$ login05-ext.leonardo.cineca.it
$ login07-ext.leonardo.cineca.it
The mandatory access to Leonardo LEONARDO is the two-factor authentication (2FA). Please refer to this link of the User Guide to activate and connect via 2FA. For information about data transfer from other computers please follow the instructions and caveats on the dedicated section section Data storage or the document Data Management.
Accounting
The accounting (consumed budget) is active from the start of the production phase. For accounting information please consult our dedicated section.
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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On LEONARDO, as on the other HPC clusters in CinecaCINECA, a a linearization policy for the usage of project budgets has been defined and implemented. The The goal is to improve the response time, giving users the opportunity of using the cpu hours assigned to their project in relation to their actual size (total amount of core-hours).
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The storage organization conforms to the CINECA infrastructure (see Section Data Storage and Filesystems).
In addition to the home directory directory $HOME, for for each user is defined a scratch area area $SCRATCH (or $CINECA_SCRATCH), a large disk for the storage of run time data and files.
A $WORK 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).
A $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 | |
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| $HOME | 0.46 PiB | 50GB per user |
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| $CINECA_SCRATCH | 41.4 40 PiB | no quota |
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| $PUBLIC | 0.46 PiB | 50GB per user |
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| $WORK | 10 30 PB | 1TB per project |
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| $FAST | 3.5PB | 1TB per project |
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- 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. For more details 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, please see the dedicated section of UG2.5: 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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$ cindataor the tool "cinQuota" available in the module cintools
$ cinQuotaFor more details about both these commands, please consult the section dedicated to how to monitor the occupancy.
Software environment
Module environment
The software modules are collected in different profiles and organized by functional categories (compilers, libraries, tools, applications, ...). The profiles are of two types: “programming” type (base and advanced) for compilation, debugging and profiling activities, and “domain” type (chem-phys, lifesc, ...) for the production activity. 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 (ibm, gnu, pgi, cuda 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 previously load the corresponding profile:
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Almost all the softwares on Leonardo LEONARDO were installed with Spack manager, which loads automatically the possible dependencies, so "autoload" command is unnecessary.
For listing all profiles you have loaded you can use the following command:
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$ modmap -m <module_name> 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.
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 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
Please note that we are still optimizing Leonardo LEONARDO software stack, and more installations may be added/replaced. Always check with "module av" (the hash in the module name can change).
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You can proceed with the sections related to Software environment, Production environment and Programming environment in the specific pages for the two partitions:
- LEONARDO Booster UserGuide
- LEONARDO Data Centric DCGP UserGuide