This paper proposes an analytical model for the optimized circuit design in an SRAM-based mixed-signal accelerator for Deep Neural Networks. The model, includes fundamental non-idealities to maintain the information content of the MAC operation, and it exploits a statistical approach to generates specification for the memory accelerator. In a case of study, the model optimization carried out with MATLAB allows to avoid three bits of ADC over-design, with large area and energy savings.
Modelling and Optimization of a Mixed-Signal Accelerator for Deep Neural Networks / Caselli, M.; Boni, A.. - (2023). (Intervento presentato al convegno International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD) tenutosi a Funchal (PT) nel 3/07/2023 - 5/07/2023) [10.1109/SMACD58065.2023.10192111].
Modelling and Optimization of a Mixed-Signal Accelerator for Deep Neural Networks
M. Caselli;A. Boni
2023-01-01
Abstract
This paper proposes an analytical model for the optimized circuit design in an SRAM-based mixed-signal accelerator for Deep Neural Networks. The model, includes fundamental non-idealities to maintain the information content of the MAC operation, and it exploits a statistical approach to generates specification for the memory accelerator. In a case of study, the model optimization carried out with MATLAB allows to avoid three bits of ADC over-design, with large area and energy savings.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
