Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL)
techniques, which rely on networks of connected simple computing units operating in …

Wearable devices are a fast-growing technology with impact on personal healthcare for both
society and economy. Due to the widespread of sensors in pervasive and distributed …

Many modern workloads, such as neural networks, databases, and graph processing, are
fundamentally memory-bound. For such workloads, the data movement between main …

Artificial intelligence (AI) edge devices prefer employing high-capacity nonvolatile compute-
in-memory (CIM) to achieve high energy efficiency and rapid wakeup-to-response with …

Many modern workloads, such as neural networks, databases, and graph processing, are
fundamentally memory-bound. For such workloads, the data movement between main …

Many modern workloads such as neural network inference and graph processing are
fundamentally memory-bound. For such workloads, data movement between memory and …

Traditional computing systems based on the von Neumann architecture are fundamentally
bottlenecked by data transfers between processors and memory. The emergence of data …

The rapid growth of artificial intelligence and the increasing complexity of neural network
models are driving demand for efficient hardware architectures that can address power …

Motivation Sequence alignment is a memory bound computation whose performance in
modern systems is limited by the memory bandwidth bottleneck. Processing-in-memory …

The saturating scaling trends of CMOS technology have fuelled the exploration of emerging
non-volatile memory (NVM) technologies as a promising alternative for accelerating data …