An Incremental Time-Domain Mixed-Signal Matrix-Vector-Multiplication Technique for Low-Power Edge-AI
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Circuits and Systems I: Regular Papers"
DOI: 10.1109/tcsi.2024.3480154
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… read more here.
Keywords: mixed signal; vector multiplication; time domain; matrix vector ... See more keywords
A native tensor-vector multiplication algorithm for high performance computing
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Parallel and Distributed Systems"
DOI: 10.1109/tpds.2022.3153113
Abstract: Tensor computations are important mathematical operations for applications that rely on multidimensional data. The tensor-vector multiplication (TVM) is the most memory-bound tensor contraction in this class of operations. This paper proposes an open-source TVM algorithm… read more here.
Keywords: vector multiplication; tensor vector; tensor; performance ... See more keywords
Reconfigurable parallel photonic matrix-vector multiplication processor based on multi-dimensional multiplexing.
Sign Up to like & getrecommendations! Published in 2025 at "Optics express"
DOI: 10.1364/oe.558224
Abstract: Matrix-vector multiplication (MVM) operations play an important role in applications such as data processing and artificial neural networks. To meet the growing demand for computing power, the photonic MVM processor provides what we believe to… read more here.
Keywords: mvm; vector multiplication; matrix vector; reconfigurable parallel ... See more keywords