.. _general_info_card:

General Information
===================

This is the main section of Cineca HPC documentation. Here you will find all the information to common Cineca's facilities. 

.. grid:: 2

   .. grid-item-card:: Access to the Systems
      :link: access_card
      :link-type: ref

   .. grid-item-card:: Users and Accounts
      :link: users_card
      :link-type: ref


HPC Service Desk
----------------

Services provided by the User Support ca be found at `Service Desk <https://www.hpc.cineca.it/user-support/>`_ website.

Cite **CINECA** in scientific publications
------------------------------------------

Users must acknowledge **CINECA** and the awarded resources in every published paper. 
Please use appropriate phrases depending on the origin of the awarded resource:

.. dropdown:: Citation List
   :animate: fade-in-slide-down
   :color: info

      * **Awards granted by ISCRA @ LEONARDO:**
        We acknowledge ISCRA for awarding this project access to the LEONARDO supercomputer, owned by the EuroHPC Joint Undertaking, hosted by CINECA (Italy) .

      * **Awards granted by EuroHPC @ LEONARDO:**
        We acknowledge the EuroHPC Joint Undertaking for awarding this project access to the EuroHPC supercomputer LEONARDO, hosted by CINECA (Italy) and the LEONARDO consortium through an EuroHPC [Extreme/Regular/Benchmark/Development/…] Access call.

      * **Awards granted by LEONARDO consortium countries @ LEONARDO:**
        We acknowledge [Grant organization, consortium country] for awarding this project access to the LEONARDO supercomputer, owned by the EuroHPC Joint Undertaking, hosted by CINECA (Italy) and the LEONARDO consortium.

      * **Awards granted by ICSC @ LEONARDO:**
        We acknowledge the ICSC for awarding this project access to the EuroHPC supercomputer LEONARDO, hosted by CINECA (Italy).

      * **Awards granted by ISCRA @ G100 and ADA Cloud:**
        We acknowledge the CINECA award under the ISCRA initiative, for the availability of high performance computing resources and support.


      To cite Leonardo architecture and the technologies adopted for its GPU-accelerated partition, please cite article:

      CINECA Supercomputing Centre, SuperComputing Applications and Innovation Department. (2024).
      “LEONARDO: A Pan-European Pre-Exascale Supercomputer for HPC and AI applications.”, Journal of large-scale research facilities, 8, A186. `DOI <https://doi.org/10.17815/jlsrf-8-186>`_.