Related papers: A device-level compact model for mushroom-type pha…
Phase-change memory devices have found applications in in-memory computing where the physical attributes of these devices are exploited to compute in place without the need to shuttle data between memory and processing units. However,…
We survey the current state of phase change memory (PCM), a non-volatile solid-state memory technology built around the large electrical contrast between the highly-resistive amorphous and highly-conductive crystalline states in so-called…
Phase change memory has been developed into a mature technology capable of storing information in a fast and non-volatile way, with potential for neuromorphic computing applications. However, its future impact in electronics depends…
The translation of emerging application concepts that exploit Resistive Random Access Memory (ReRAM) into large-scale practical systems requires realistic, yet computationally efficient, empirical models that can capture all observed…
Compact device models play a significant role in connecting device technology and circuit design. BSIM-CMG and BSIM-IMG are industry standard compact models suited for the FinFET and UTBB technologies, respectively. Its surface potential…
We present a behavioral compact model of 3D NAND flash memory for integrated circuits and system-level applications. This model is easy to implement, computationally efficient, fast, accurate and effectively accounts for the different…
This work reports a compact behavioral model for gated-synaptic memory. The model is developed in Verilog-A for easy integration into computer-aided design of neuromorphic circuits using emerging memory. The model encompasses various forms…
Phase change memory (PCM) relies on a reversible transition between amorphous and crystalline states of a material, and stands as a promising candidate for next-generation, energy-efficient data storage and neuromorphic hardware. Here, we…
Y-Flash memristors utilize the mature technology of single polysilicon floating gate non-volatile memories (NVM). It can be operated in a two-terminal configuration similar to the other emerging memristive devices, i.e., resistive…
Phase-change memory (PCM) is a scalable and low latency non-volatile memory (NVM) technology that has been proposed to serve as storage class memory (SCM), providing low access latency similar to DRAM and often approaching or exceeding the…
Phase change memory (PCM) is an emerging high speed, high density, high endurance, and scalable non-volatile memory technology which utilizes the large resistivity contrast between the amorphous and crystalline phases of chalcogenide…
We have computationally demonstrated logic function implementations using lateral and vertical multi-contact phase change devices integrated with CMOS circuitry, which use thermal cross-talk as a coupling mechanism to implement logic…
In recent years, the energy consumption of computing systems has increased and a large fraction of this energy is consumed in main memory. Towards this, researchers have proposed use of non-volatile memory, such as phase change memory…
Computer simulations have long been key to understanding and designing phase-change materials (PCMs) for memory technologies. Machine learning is now increasingly being used to accelerate the modelling of PCMs, and yet it remains…
As transistor-based memory technologies like dynamic random access memory (DRAM) approach their scalability limits, the need to explore alternative storage solutions becomes increasingly urgent. Phase-change memory (PCM) has gained…
Phase-change materials (PCMs) are the subject of considerable interest because they have been recognized as potential active layers for next-generation non-volatile memory devices, known as Phase Change Random Access Memories (PRAMs). By…
Resistive memories are outstanding electron devices that have displayed a large potential in a plethora of applications such as nonvolatile data storage, neuromorphic computing, hardware cryptography, etc. Their fabrication control and…
Volatile memristors have recently gained popularity as promising devices for neuromorphic circuits, capable of mimicking the leaky function of neurons and offering advantages over capacitor-based circuits in terms of power dissipation and…
Machine learning-based compact models provide a rapid and efficient approach for estimating device behavior across multiple input parameter variations. In this study, we introduce two reverse-design algorithms that utilize these compact…
The goal of this thesis is to gain new insights into the drift phenomenon and identify strategies to mitigate it. An extensive experimental characterization of PCM devices and in particular drift forms the foundation of each chapter. With…