Speaker
TRAN, Nhan Viet
(Fermi National Accelerator Lab. (US))
Description
We discuss applications and opportunities for the machine learning in real-time embedded systems in particle physics. This talk will focus on how to implement machine learning algorithms in systems with FPGAs and ASICs for a variety of use-cases. We will review essential ideas for designing and optimizing efficient algorithms in hardware and emerging tool flows to accelerate algorithm development. We will then explore a few examples spanning different application spaces such as front-end data compression in rad-hard environments to powerful trigger reconstruction algorithms to controls of particle accelerators.
Primary author
TRAN, Nhan Viet
(Fermi National Accelerator Lab. (US))
