Crossbar Array

Crossbar arrays are emerging as a key technology for accelerating deep neural network (DNN) computations through in-memory computing (IMC), aiming to improve energy efficiency and speed. Current research focuses on optimizing DNN architectures (like Vision Transformers and convolutional networks) for crossbar implementation, mitigating hardware limitations (e.g., non-idealities in memristor devices, ADC energy consumption), and developing novel training algorithms that account for crossbar characteristics. This work holds significant promise for enabling more efficient and powerful AI applications, particularly in resource-constrained environments like edge devices, by reducing energy consumption and latency.