HPC is a well-established technology capable of solving and simulating complex problems in a wide variety of contexts-from plasma physics to molecular dynamics to weather forecasting, to name a few.
Traditionally, classical HPC has been applied, with excellent results, to solve problems by optimizing the two-benchmark metrics time-to-solutions and energy-to-solutions but they have shown limits for some problems, called non-polynomial (NP). In this type of problems quantum machines show they can radically speed up computation times.
However, these systems are as of now in a prototypal phase, with low TRL indices and without a defined standard. These systems collectively form a multitude of possible technological paths among which it is expected that in the future the architectures that will prove to be more stable and able to scale toward “quantum supremacy” may emerge.
In fact, classical HPC and QC are not at all antithetical systems as much as they can work side by side in solving complex problems; they should be thought of as two sides of the same coin if the ‘correct’ separation of the quantum algorithm parts from the classical algorithm parts is implemented and orchestrated among the two architectures so that they can cooperate efficiently.
Contributions will address, but are not limited to, the following topics:
- Whether at present makes sense to start considering how to do this interfacing, what aspects should be considered, both from a software and a hardware point of view.
- Understanding what the critical issues are to start working in this direction and what the benefits and potential targets will be.
- How and when heterogeneous technologies in QC systems will converge toward integration with classical computers and what the limitations may be.
- Status of the art for Quantum Computing technologies, presenting academics and companies results in this field.
- Description of application and use cases, first results with emulators and quantum systems, in different fields of research.