One of the special types of Computer Memory is said to be as Content Addressable Memory. It is also called as associative array or associative storage, associative memory which can be frequently used in very high speed searching applications such as databases, associative computing, lookup tables and networking. CAM is one type of functional memory which contains huge amount of stored data wher...

In this paper, resistive random access memory (RRAM)-based crossbar arrays with the cell structure of Pt/[AlO y /HfO x ] m /TiN were fabricated by using atomic layer deposition (ALD) technique. The RRAM devices in the arrays show excellent performances such as good uniformity and high reliability. Based on the fabricated RRAM array, a complete set of basic logic operations including NOR and XNO...

This brief presents an energy-efficient and high-performance XNOR-bitcount architecture exploiting the benefits of computing-in-memory (CiM) unique properties spin-transfer torque magnetic RAM (STT-MRAM) based on double-barrier tunnel junctions (DMTJs). Our work proposes hardware algorithmic optimizations, benchmarked against a state-of-the-art CiM-based design. Simulation results show that our...

Specialized hardware accelerators beyond von-Neumann, that offer processing capability in where the data resides without moving it, become inevitable data-centric computing. Emerging non-volatile memories, like Ferroelectric Field-Effect Transistor (FeFET), are able to build compact Logic-in-Memory (LiM). In this work, we investigate probability of error (Perror) FeFET-based XNOR LiM, demonstra...

Quantum-dot cellular automata (QCA) are nanoscale digital logic constructs that use electrons in arrays of quantum dots to carry out binary operations. In this paper, a basic building block for QCA will be proposed. The proposed basic building block can be customized to implement classical gates, such as XOR and XNOR gates, and reversible gates, such as CNOT and Toffoli gates, with less cell co...

Recently, building an efficient and robust model for object detection has attracted the attention of vision community. Although binary networks have a fast inference speed, they cannot be used directly on mobile devices such as unmanned aerial vehicles (UAVs) because their low accuracy. Different from improving accuracy network by adjusting structure or update gradient, we propose improved neur...