Giacomo Pedretti

Multi-primitive in-memory computing for Monte Carlo tree search

Tergel Molom-Ochir, Benjamin F. Morris, Yintao He, Archit Gajjar, Giacomo Pedretti, Hai Helen Li, et al.

Monte Carlo tree search (MCTS) enables artificial intelligence (AI) decision-making, but requires 55-300 W on conventional processors, limiting edge deployment. In-memory computing (IMC) is energy-efficient on regular workloads but has been considered incompatible with irregular…Read more

Neuromorphic technologies for novel hardware AI

Gianluca Milano, Giacomo Pedretti, Nagarajan Raghavan

Continuous-time nonlinear closed-loop in-memory computing for high-accuracy massive MIMO detection

Piergiulio Mannocci, Giacomo Pedretti, Fabian Böhm, Thomas Van Vaerenbergh

Analog in-memory computing (IMC) has emerged as a promising approach for accelerating matrix operations by exploiting the intrinsic physics of memory arrays. To date, however, most IMC architectures have focused on linear algebra workloads in which computation is encoded in the e…Read more