Quantum computing (QC) enjoys great attention at the highest levels of research and economic policy on a national, European and international level. It promises unprecedented potential for important computing tasks such as simulations in chemistry or materials science, optimization and machine learning. With this potential, QC is increasingly attracting interest from industry and scientific groups that use high performance computing (HPC) for their applications. These pilot users are primarily interested in testing whether available quantum computers today or in the foreseeable future are suitable for simulating increasingly complex systems, analyzing large data sets using machine learning methods or performing the hardest optimization task.
Potential applications are materials design for batteries, drug design, portfolio optimization in finances, risk optimization for insurances, flight and train scheduling, hotel reservation, traffic flow prediction, power trading and scheduling, image-based medical diagnostics, and many more. Hence, QC can considerably change science, industry, economy and our everyday life. Although QC still lags behind classical computing for most practical applications, its completely novel computational approach could revolutionize scientific computing and enable discoveries across a diverse range of fields beyond the reach of classical methods.
The research in applications of QC to real-world problems, however, is still in its infancy. Therefore, the early entry into the practical application of QC is of utmost urgency in order to evaluate QC as a new computer technology. The prerequisite for this is early access to quantum computers at the forefront of development, taking into account the different technical approaches. Another prerequisite is the integration of quantum computers into HPC infrastructures in order to enable the execution of quantum-classical hybrid computing models on the integrated HPC-QC infrastructure.
A first argument for hybrid quantum-classical computations is that most applications in QC are today realized algorithmically with a high degree of hybridity. In hybrid computations, classical algorithms are combined with quantum algorithms (e.g. quantum optimizers for machine learning or variational quantum algorithms). Another argument for hybrid computing arises from the side of HPC when considering the energy consumption of modern supercomputers and the potential energy saving through the use of quantum computers.
The HPCQS ("High Performance Computer and Quantum Simulator hybrid") project is building a European pilot infrastructure that will provide tightly coupled systems of quantum simulators (QSs), which are analog quantum computers, and supercomputers to enable quantum HPC hybrid computing. Two such modular quantum HPC systems with identical QSs from Pasqal, each comprising more than 100 qubits, are being installed and federated at CEA/TGCC and FZJ/JSC (see Fig. 1). The programming and access platform is based on Atos' QLM system and uses the Modular Supercomputing Architecture concept developed by JSC and ParTec for tight integration with the HPC system. The infrastructure is developed in a co-design process together with selected use cases. The goal of HPCQS is to prepare European research and industry for the federated use of QSs to address the most demanding computational challenges. For this purpose, use cases are developed to demonstrate the relevance of the HPCQS approach for scientific and industrial applications. Courses for both scientific and industrial user needs are offered to support access and use of the HPCQS infrastructure, as well as training materials, and user manuals.
The deep integration of QSs into high-end HPC systems is unique in the world.
