Tutorial on Variational Quantum Algorithms for Resource Management in Cloud/Edge Architectures

This tutorial offers a practical introduction to the fascinating world of quantum computation and its application to optimization and machine learning problems. The participants will acquire hands-on experience in developing hybrid "Variational Quantum Algorithms", which combine classical and quantum computation, and in running them both on simulators and real quantum hardware provided by leading ICT companies. As a concrete use-case, of specific interest for the HPDC community, the tutorial will discuss the optimal assignment and scheduling of resources on the different nodes and layers of a Cloud/Edge architecture, a problem that is known to have NP-hard complexity.The tutorial will show how Variational Quantum Algorithms can become a viable alternative to classical algorithms to solve the resource assignment problem. The participants will be driven, step-by-step, to the reformulation of the problem in terms of an Ising problem, which is then solved through two variational quantum algorithms, i.e., Quantum Approximate Optimization Algorithm (QAOA) and Variational Quantum Eigensolver (VQE), by exploiting the libraries of IBM Qiskit and Xanadu Pennylane. Finally, the tutorial will discuss the perspectives on the use of quantum computation for this and other scenarios, and the possible avenues for future academic research and industrial developments.