This paper presents a novel 3D folded capacitive synaptic crossbar array designed for in-
memory computing architectures. In this architecture, the bitline is folded over the wordline to …

PoolFormer is a subset of Transformer neural network with a key difference of replacing
computationally demanding token mixer with pooling function. In this work, a memristor …

The memristor crossbar, with its exceptionally high storage density and parallelism, enables
efficient vector matrix multiplication (VMM), significantly improving data throughput and …

In-memory computing (IMC) can accelerate data-intensive tasks, such as matrix-vector
multiplication (MVM) or artificial neural networks (ANNs) inference, by means of the …

PoolFormer is a type of neural network architecture that is abstracted from Transformer
where the computationally heavy token mixer module is replaced with simple pooling …

In this work, the requirement of using high‐precision (HP) signals is lifted and the circuits for
implementing deep learning algorithms in memristor‐based hardware are simplified. The …

The surge in AI usage demands innovative power reduction strategies. Novel Compute-in-
Memory (CIM) architectures, leveraging advanced memory technologies, hold the potential …