Tecniche Di Machine Learning Con Dispositivi FPGA per Gli Esperimenti Di Fisica Delle Particelle

Scientific Programme

Programma

Main Topics

• Introduction to FPGA
• Machine Learning Application in Particle Physics Experiment
• Deep Learning with FPGA
• Xilinx FPGA and solutions overview
• HLS4ML
• Bond Machine
• Ml/AI with Intel FPGA
• Vitis AI

Organizing Committee

Riccardo Travaglini (chair)
Daniele Bonacorsi (program consultant)
Mariella Gangi (logistic and INFN education commission link)
Marco Lorusso (program consultant and IT support)
Paolo Veronesi (IT support)
Antonella Monducci (IT support)

Acknowledgements

Special Thanks to who facilitated this course (in alphabetical order!)

• Alessandro Costantini
• Cristina Duma
• Diego Michelotto
• Felice Pantaleo
• Maurizio Pierini
• Davide Salomoni

Also thanks to Xilinx University Program for support

Presenters

Dr. Thea Aarrestad (ETH)
Dr. Vladimir Loncar (CERN)
Dr. Marco Lorusso (Physics and Astronomy Dpt. University of Bologna- INFN-BO)
Dr. Mirko Mariotti (Physics and Geology Dpt. University of Perugia - INFN-PG)
Dr. Jennifer Ngadiuba (CALTECH)
Dr. Sioni Summers (CERN)
Dr. Riccardo Travaglini (INFN-BO)