Why ever increasing models and how to handle them

Deep learning is rapidly and radically transforming the way science and industry use data to solve problems. Deep neural network models have proven to be powerful tools for extracting information from data in a large number of domains. As these models grow in complexity to solve increasingly challenging problems with larger and larger datasets, the need for scalable methods and software to train them grows too.

This presentation aims to provide participants with a practical understanding of deep learning on large systems, including fundamental concepts, optimization opportunities, and scalability techniques.

Giuseppe Fiameni: HPC/AI at NVIDIA

Giuseppe Fiameni is a Solution Architect and Data Scientist at NVIDIA where he oversees the NVIDIA AI Technology Center in Italy, a collaboration among NVIDIA, CINI and CINECA to accelerate academic research in the field of Artificial Intelligence through collaboration projects. He has been working as HPC specialist at CINECA, the largest HPC facility in Italy, for more than 14 years providing support for large-scale data analytics workloads.

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