HPCQS High Performance Computer and Quantum Simulator hybrid (DFM.AD002.144)
Area tematica
Scienze fisiche e tecnologie della materia
Area progettuale
Scienze e tecnologie quantistiche (DFM.AD002)Struttura responsabile del progetto di ricerca
Istituto nazionale di ottica (INO)
Altre strutture che collaborano al progetto di ricerca
Responsabile di progetto
FILIPPO CARUSO
Telefono: 05523081
E-mail: filippo.caruso@ino.cnr.it
Abstract
The aim of HPCQS is to prepare European research, industry and society for the use and federal operation of quantum computers and simulators. These are future computing technologies that are promising to overcome the most difficult computational challenges. HPCQS is developing the programming platform for the quantum simulator, which is based on the European ATOS Quantum Learning Machine (QLM), and the deep, low-latency integration into modular HPC systems based on ParTec's European modular supercomputing concept. A twin pilot system, developed as a prototype by the European company Pasqal, will be implemented and integrated at CEA/TGCC (France) and FZJ/JSC (Germany), both hosts of European Tier-0 HPC systems. The pre-exascale sites BSC (Spain) and CINECA (Italy) as well as ICECH (Ireland) will be connected to the TGCC and JSC via the European data infrastructure FENIX. It is planned to offer quantum HPC hybrid resources to the public via the access channels of PRACE. To achieve these goals, HPCQS brings together leading quantum and supercomputer experts from science and industry, thus creating an incubator for practical quantum HPC hybrid computing that is unique in the world.
Obiettivi
The aim of HPCQS is to prepare European research, industry and society for the use and federal operation of quantum computers and simulators. HPCQS brings together leading quantum and supercomputer experts from science and industry, thus creating an incubator for practical quantum HPC hybrid computing that is unique in the world. The HPCQS technology will be developed in a co-design process together with selected exemplary use cases from chemistry, physics, optimization and machine learning suitable for quantum HPC hybrid calculations.
Activities:
Design of the architecture for the hybrid classical-quantum computing infrastructure
Quantum Algorithms towards the use-case on Quantum Machine Learning (coordinated by CNR-INO)
Data inizio attività
01/12/2021
Parole chiave
quantum simulator, hybrid quantum-HPC computation, federated quantum-HPC infrastructure
Ultimo aggiornamento: 15/05/2025