The PPHA group focuses on the research of SW and HW solutions for the development, deployment and efficient execution of parallel and heterogeneous computing systems required to process huge amounts of data across the compute continuum, addressing edge, cloud and HPC. The group addresses the complete system stack: (1) HW solutions, by researching on highly parallel and energy efficient HW accelerators for an optimised execution; (2) SW solutions, by researching on parallel programming models and software frameworks capable of efficiently exploit the performance capabilities of the underlying HW; and (3) advanced AI and data-analytics methods optimised for parallel execution. PPHA research focuses not only on performance, but also on correctness, real-time, resiliency and energy-efficient requirements imposed by the system constraints. These solutions are being applied to a wide number of application domains, including astronomy, bioinformatics, smart cities, automotive and space.