Quantum Computing: Programming & Software Aspects

Top500 Supercomputers are currently composed of processors, accelerators (such as GPUs) and an interconnect. These platforms are in constant evolution to provide more performance. To this aim, several kinds of accelerators/processors are emerging, such as neuromorphic and quantum processors. The latter are one of the most promising technologies as they may provide exponential speed-up for certain tasks.
Prototypes for these quantum processors are available from firms such as Intel, Google and IBM.

During more than 30 years, classical software and applications have been developed to expand the scope of classical processors. Even recently, applications such as machine learning have pushed back the limits of classical computing.

Similarly, the near-to-medium term quantum applications have to be precisely characterized. With the Quantum Learning Machine (QLM), Atos provides tools to analyze and to disclose the potential advantage of realistic quantum processors. The aim is to create a full software stack for quantum platforms with hardware analysis (noise, architecture), general and hardware-specific circuit optimizations, to investigate the different quantum hardwares and the distributed platform architectures, as well as to develop applications and unified interfaces.

Target Audience: Developers, Architects
Prerequisites: Knowledge in Software Engineering
Level: Introductory