Racetrack memory (RTM) is a novel spintronic memory-storage technology that has the
potential to overcome fundamental constraints of existing memory and storage devices. It is …

Recurrent Neural Networks (RNNs) are a class of machine learning algorithms used for
applications with time-series and sequential data. Recently, there has been a strong interest …

In this paper, we propose MRIMA, as a novel magnetic RAM (MRAM)-based in-memory
accelerator for nonvolatile, flexible, and efficient in-memory computing. MRIMA transforms …

Recent trends of increasing core-count and bandwidth/memory wall have motivated
researchers to explore novel memory technologies for designing processor components …

The increasing power consumption in the existing computation architecture presents grand
challenges for the performance and reliability of very‐large‐scale integrated circuits …

In‐memory computing is a computing scheme that integrates data storage and arithmetic
computation functions. Resistive random access memory (RRAM) arrays with innovative …

This introductory tutorial provides an overview of business process simulation and how it
works. Descriptions of modeling elements and model performance measures are presented …

There is great attention to develop hardware accelerator with better energy efficiency, as
well as throughput, than GPUs for convolutional neural network (CNN). The existing …

In this paper, we propose an energy-efficient reconfigurable platform for in-memory
processing based on novel four-terminal spin Hall effect-driven domain wall motion devices …

In this paper we propose a Highly Flexible InMemory (HieIM) computing platform using STT
MRAM, which can be leveraged to implement Boolean logic functions without sacrificing …