CINECA Summer School for HPC + AI 2026

The program introduces the principles and practical use of diverse computing architectures, with particular attention to the combined use of CPUs and GPUs to achieve improved computational performance and efficiency. In addition, fundamental and applied aspects of deep learning are addressed, including model design, training workflows, and strategies for scaling from single-GPU environments to distributed systems.

Participants engage with core topics such as parallel programming models, hardware-aware optimization strategies, scalable software design, and efficient deep learning training techniques. The course combines theoretical lectures with hands-on laboratory sessions and interactive discussions, enabling direct application of the concepts introduced. The overall objective is to provide a solid foundation for leveraging heterogeneous computing and deep learning across a range of applications, from scientific research to industrial innovation.

Skills Covered

C/C++, Fortran, Python

Intended for: Research Institutions, schools and universities

Area: Languages & Techniques

Length: 10 dd