Institutional resources available on Trantor


The cluster includes several different node types, organized in homogeneous groups:

  • Daneel : 3 nodes, each equipped with 2 Intel Xeon CPUs, 36 cores (18 cores per socket), 1.5 TB of RAM (about 42 GB/core), 6TB local scratch space and 4 Tesla NVIDIA GPUs with 32 GB of RAM (each).
  • Hal : 2 nodes, each equipped with 4 Intel Xeon CPUs, 112 cores (28 cores per socket), 3 TB of RAM (about 28 GB/core) and 11TB local scratch space.
  • Helicon : 14 nodes, each equipped with 2 Intel Xeon CPUs, 12 cores (6 cores per socket), 20 GB of RAM (about 1.7 GB/core). No local scratch space, only a scratch area shared among the nodes.
  • Artes : 6 nodes, each equipped with 2 Intel Xeon CPUs, 32 cores (16 cores per socket) and 128 GB of RAM (4 GB/core). The scratch space is shared among the nodes. The use of these nodes is restricted. To access, send a request to Professor Chiara Cappelli.

Storage - Clustered NAS with Infiniband backend network, 40 GE frontend network and 3.0 PB of raw space.

In addition, Trantor acts as front end node for group owned resources, open to computation only to specific groups. See the page " Group owned resources accessible from Trantor " for details.

Running computations on the cluster

All calculations MUST be submitted as Jobs to the Portable Batch System (PBS) scheduling system, for their execution on the compute nodes.

Running interactively on the "head-nodes" is FORBIDDEN. It is also STRICTLY FORBIDDEN to run your computations on the compute nodes bypassing the job submission mechanism.

You can find a brief introduction to PBS at the following Web page: Submitting, inspecting and cancelling PBS Jobs

Scratch Areas

Every user has a scratch space on every computing node, under /scratch/$USER. This area is a temporary storage designed for Jobs’ I/O operations. When possible, this storage area is allocated on the local hard drives of the compute nodes, thus providing a higher bandwidth and a lower latency than NFS mount points. This is the case, for example, of Daneel and Hal nodes. Helicon and Artes, instead, are only equipped with a "shared" scratch area: this is a NFS storage space which is accessible by all the Helicon and Artes nodes.

You can find further details and important notes on the use of scratch areas at the following Web page: Submitting, inspecting and cancelling PBS Jobs - Scratch Areas

Project areas

Is it possible to request additional storage areas on the NAS for storing data related to specific research projects and sharing files among projects members. Such additional storage will be reserved for a limited amount of time (max 1 year).

In the 'Forms' page you can find a form to request, to the Committee and the Staff, the creation of a project area. The request must be submitted by tenured personnel and must include the list of users that can access the area.

Data protection

Our storage system employs a redundant, distributed file system to avoid data loss in the case of a limited hardware failure (disks in a node or entire nodes). Furthermore, snapshots of the content of homes and projects directories are periodically recorded on the storage system and retained for several months, thus allowing to retrieve files that were deleted or overwritten by accident.

Keep in mind, however, that snapshots are not an actual backup mechanism. In fact, while a backup is a full copy of the data stored on a separate storage device (preferably located on a different location), a snapshot is a sort of immutable “photo” of the file system, generated instantaneously and incrementally on the same storage device. With respect to snapshots, backups allow the recovery of the data even in the case of catastrophic events. On the other hand, backups require a separate large-capacity storage device, a significant amount of time and must be performed on data at rest.

Finally, our storage system does not preserve hard-links in snapshots. That means that if multiple files points to the same blocks of data on disk, only one of those files will be preserved in snapshots (you can find a gentle introduction to hard-links here ). That fact implies that, in those scenarios where hard-links are in use, there may be loss of information when recovering files from snapshots (because only one hard-link for each data file would be recovered). Examples of such scenarios include:

  • Software installations that make use of hard-links such as (conda virtual environments).
  • Hard-links manually created by users.
  • Files generated as output by applications, if the software creates hard-links (e.g. as a way to avoid data duplication). Fortunately, such cases are quite rare.
This limitation cannot be circumvented, so please avoid the use of hard-links as much as possible and use soft-links instead.


Most of the software installed on the cluster is made available by means of Environment Modules . Use the module avail command to get the list of the currently available modules:

[hpcstaff@trantor01 ~]$ module avail ------------ /cluster/shared/modules/modulefiles/compilers --------- cmake/3.10.1 gcc/7.3.0 gcc/8.3.0 cmake/3.18.2 gcc/9.3.0 gcc/10.2.0 ------------- /cluster/shared/modules/modulefiles/libs ------------- blas-lapack/gcc-10.2.0/3.9.0 libint/gcc-8.3.0/2.6.0 boost/gcc-8.3.0/1.74.0 libint/gcc-8.3.0/2.7.0-beta.1 boost/header-only/1.74.0 libint/gcc-8.3.0/2.7.0-beta.6 cuda/10.2 libxc/gcc-8.3.0/5.0.0 cuda/11.0.2 openmpi/gcc-8.3.0/4.0.4 eigen/3.3.7 openmpi/gcc-9.3.0/4.0.4 fftw/gcc-8.3.0/3.3.8 openmpi/gcc-10.2.0/4.0.4 fftw/gcc-9.3.0/3.3.8 scalapack/openmpi-4.0.4/gcc-10.2.0/2.1.0 fftw/gcc-10.2.0/3.3.8 ------------ /cluster/shared/modules/modulefiles/apps -------------- gnuplot/5.2.8 gromacs/gcc-8.3.0/2020.3 openbabel/2.4.1

You can then use the module load 'modulename' to "load" a specific module. By doing so, your shell environment will be set up to use that particular software. This usually consists in properly setting a few environment variables (such as PATH, CPATH, LD_LIBRARY_PATH etc.) and loading the related dependencies. For example, doing module load gromacs/gcc-8.3.0/2020.3 will load the software needed to run this version of Gromacs, such as OpenMPI and CUDA. It will also add the binaries path of Gromacs 2020.3 to your environment and set the relative libraries and man paths, plus other variables specific to this software.

It is important to note that the module load command can also be used in job scripts, so to properly set up the environment prior to a computation (more info on jobs submission with PBS here).

Other commonly used module commands are the following:

  • module list : prints the currently loaded modules.
  • module unload modulename : reverts the modifications that were applied to your shell environment during the loading of the specified module.
  • module purge : unloads all the modules.
  • module help modulename : prints a concise description of the module.
Please note that there is no module for Python 3 and related libraries, since the Conda utility provides a better alternative. A brief introduction to using Conda on the Trantor cluster can be found here.

Wolfram Mathematica

Wolfram Mathematica is available on Trantor.

In accordance to the terms of the license subscribed by Scuola Normale Superiore, the use of this software is restricted to SNS students and research staff only. Access to the software must be explicitly requested by writing to

Once your account is configured, you will be able to use the software by loading the "mathematica/<version number>" module and executing one of the following commands:

  • MathKernel : starts the Mathematica Kernel.
  • Mathematica : starts the GUI version of Mathematica. To be used only on nodes equipped with a desktop environment (e.g.

Please remember that running software on head-nodes is allowed only for light computations. Computationally intensive tasks MUST be executed on compute nodes, by submitting them as a job to the PBS scheduling system (see Submitting, inspecting and cancelling PBS Jobs for details). Jobs with heavy footprints being executed on the head nodes may be cancelled without warning.

Wolfram Mathematica can be used for academic purposes only and its use is subject to the Wolfram Mathematica License Agreement:
Carefully read the terms and conditions before using the software.

Furthermore, when publishing academic or research papers for which Mathematica was used, Wolfram Mathematica should be appropriately cited as a reference and/or described in a methods section.

Finally note that, at this time, Mathematica on Trantor should be considered experimental. You are advised to save the results of your work frequently! Please report any problem you encounter.

MathWorks MATLAB

MATLAB Parallel Server is available on the Trantor cluster, allowing to execute long-running CPU and/or GPU intensive computations on high-performance compute nodes.
Jobs submission and results retrieval is performed directly from the MATLAB instance running on your personal workstation.

In accordance with the terms of the license subscribed by Scuola Normale Superiore, the use of this service is restricted to SNS students and research staff only. In addition, access to the service must be explicitly requested by writing to

MathWorks products can be used for academic purposes only and their use is subject to the MathWorks, Inc. Software License Agreement and Program Offering Guide. You can read both documents by selecting the Help → Terms of Use menu entry from the MATLAB toolbar, or by opening the file license_agreement.txt stored in your MATLAB installation folder. Carefully read the terms and conditions before using the software.

Refer to the user guide for details on the required configuration and instructions on how to submit jobs and retrieve results.

Compile your software

To compile your software, the first step is to load the module of the desired compiler. Then load the software libraries you need (e.g. OpenMPI, CUDA, LAPACK etc.). For each library, make sure to load a version which has been compiled with the same compiler you plan to use, otherwise you may encounter compatibility issues! To this end, most of the libraries modules contain in their name the compiler they are compatible with. E.g. "fftw/gcc-8.3.0/3.3.8" is the name of the module for using the FFTW library version 3.3.8 compiled with GCC 8.3.0.

Example: $ module load gcc/8.3.0 $ module load fftw/gcc-8.3.0/3.3.8 $ module load openmpi/gcc-8.3.0/4.0.4

If you need a library which is not currently available, or if you need to compile an already existing library with a different compiler, please send a request to the staff (see below).

Intel OneAPI compilers

The Intel OneAPI compilers suite is available on Trantor. You can use it by loading the module intel/2021.1.1 and any relevant module under intel/*.

The licence is "single fixed Multi-Node", meaning that only one person at a time can use the compiler, from any computer.

Since the suite has many tools and libraries, we decided to install only some of them, to avoid cluttering. Please contact us if you need something that is not installed.


A (customized) installation of JupyterHub is available at the following URL:

It provides a user-friendly GUI to create one or more Jupyter notebook servers and scheduling their execution as PBS Jobs. If you are interested in using JupyterHub@Trantor, please carefully read the User Guide .

User support

To activate an account to access the Trantor cluster, send an email to HPC Staff. We will provide you a one-time password that you will have to change at first login. Also, please take care to provide an email address (one you actually use) that will be added to the cluster mailing list, so to stay informed about news and maintenance notices.
If you notice any problem, please contact the staff by writing to HPC Staff. Please contact the staff and NOT a single member. If your problem can be redirected to someone in particular, we'll let you know.