Parallel, distributed, and network-based processing has undergone impressive changes over recent years. New architectures, advanced programming models, improved efficiency, and novel application domains have rapidly become the central focus of this discipline. These changes are often a result of the cross-fertilization of parallel and distributed computational paradigms with other rapidly evolving technologies in different disciplines. It is paramount to review and assess these new developments in relation to the recent research achievements in various areas of parallel and distributed computing, considering both industrial and scientific points of view.

Often, these technologies can affect our daily life, and several are the applications into which parallel computers find full usage: the increasingly wide usage of biomedical image processing, often in real-time and with the application of complex machine- and deep-learning algorithms, is only one of the most evident examples of this. Another example is environmental monitoring with the full integration of cloud architectures. Other fields into which these approaches find application include commercial/financial predictions, weather and climate forecasts, computational physics/fluid dynamics, and healthcare, wellness, and personal monitoring.

The Summer School offers an intensive program on the entire hardware and software stack. This co-design is essential for designing High-Performance Computing (HPC) solutions and accelerating data-centric workloads.

This edition will focus on RISC-V architecture and the most recent technologies for HPC interconnect. The curriculum aims to boost participants' capabilities in utilizing HPC for complex and data-heavy scientific tasks, covering everything from the basics of computer architecture and the design of high-performance processors to parallel computing.

On the software front, the course will address the design of scalable parallel algorithms and the use of programming models and tools crucial for enhancing HPC application performance, including practical hands-on sessions focusing on OpenMP, GPU programming, and MPI. We will introduce attendees to HPC trends like machine learning integration and extra-functional properties like energy efficiency and reliability.

By the end of the school, attendees will have a thorough understanding of the HPC field, from hardware specifics, particularly RISC-V, to software development challenges and strategies, enabling them to contribute significantly to HPC's future in their careers.

This edition the school offers a mentoring program to support PhD students in their career path and research by receiving feedback from the lecturers. 

The course addresses a broad audience, including PhD students, young researchers, professional engineers operating in the industry, and outstanding undergraduate students.