The discovery of ferroelectricity in oxides that are compatible with modern semiconductor
manufacturing processes, such as hafnium oxide, has led to a re-emergence of the …

Compute-in-memory (CIM) is a new computing paradigm that addresses the memory-wall
problem in hardware accelerator design for deep learning. The input vector and weight …

From our own experience, we know that there is a gap to bridge between the scientists
focused on basic material research and their counterparts in a close-to-application …

Data-centric applications are pushing the limits of energy-efficiency in today's computing
systems, including those based on phase-change memory (PCM). This technology must …

Superlattice (SL) phase change materials have shown promise to reduce the switching
current and resistance drift of phase change memory (PCM). However, the effects of internal …

This invited paper surveys the recent progresses of compute-in-memory (CIM) prototype
chip designs with emerging nonvolatile memories (eNVMs) such as resistive random access …

Abstract Phase-Change Memory (PCM) is one of the most recent technologies to enter the
embedded memory market for consumer-and automotive-grade applications. However …

Under the von Neumann computing architecture, the edge devices used for artificial
intelligence (AI) and the Internet of Things (IoTs) are limited in terms of latency and energy …

Microprocessors use static random-access memory (SRAM) cells in the cache memory
design. As a part of the central computing component, their performance is critical. Modern …

Repeated off-chip memory accesses to DRAM drive up operating power for data-intensive
applications, and SRAM technology scaling and leakage power limits the efficiency of …