Work

An Incremental Time-Domain Mixed-Signal Matrix-Vector-Multiplication Technique for Low-Power Edge-AI

Year: 2024

Type: article

Abstract: This paper proposes a time-domain mixed-signal computing architecture for Matrix-Vector Multiplication suited for embedded in-memory computing applications. The system leverages the low data rate of sensors’ data in embedded AI applications to target an energy-efficient implementation of the matrix-vector multiplication array. The mixed-signal computing scheme relies on incremental time-domain multiply-and-accumulate operations using switched current sources. The concept is demonstrated on a 28nm FDSOI prototype chip of a 100$\times $4 compute array that shows a 15.8TOPS/W energy efficiency for 5-bit MAC operations. Extrapolating the array to 100$\times $100 computing units leads to a 99.2TOPS/W energy efficiency.

Source: IEEE Transactions on Circuits and Systems I Regular Papers

DOI: 10.1109/tcsi.2024.3480154

Authors: Kévin Hérissé, Benoit Larras, Bruno Stefanelli, Andreas Kaiser, Antoine Frappé