329 research outputs found
Cryogenic Memory Technologies
The surging interest in quantum computing, space electronics, and
superconducting circuits has led to new developments in cryogenic data storage
technology. Quantum computers promise to far extend our processing capabilities
and may allow solving currently intractable computational challenges. Even with
the advent of the quantum computing era, ultra-fast and energy-efficient
classical computing systems are still in high demand. One of the classical
platforms that can achieve this dream combination is superconducting single
flux quantum (SFQ) electronics. A major roadblock towards implementing scalable
quantum computers and practical SFQ circuits is the lack of suitable and
compatible cryogenic memory that can operate at 4 Kelvin (or lower)
temperature. Cryogenic memory is also critically important in space-based
applications. A multitude of device technologies have already been explored to
find suitable candidates for cryogenic data storage. Here, we review the
existing and emerging variants of cryogenic memory technologies. To ensure an
organized discussion, we categorize the family of cryogenic memory platforms
into three types: superconducting, non-superconducting, and hybrid. We
scrutinize the challenges associated with these technologies and discuss their
future prospects.Comment: 21 pages, 6 figures, 1 tabl
Recommended from our members
Organic electronics for neuromorphic computing
Neuromorphic computing could address the inherent limitations of conventional silicon technology in dedicated machine learning applications. Recent work on silicon-based asynchronous spiking neural networks and large crossbar-arrays of two-terminal memristive devices has led to the development of promising neuromorphic systems. However, delivering a compact and efficient parallel computing technology, such as artificial neural networks embedded in hardware, remains a significant challenge. Organic electronic materials offer an attractive alternative for such systems and could provide biocompatible and relatively inexpensive neuromorphic devices with low-energy switching and excellent tunability. Here, we review the development of organic neuromorphic devices. We consider different resistance switching mechanisms, which typically rely on electrochemical doping or charge trapping, and discuss the challenges the field faces in implementing low power neuromorphic computing, which include device downscaling, improving device speed, state retention and array compatibility. We highlight early demonstrations of device integration into arrays and finally consider future directions and potential applications of this technology
Memristors : a journey from material engineering to beyond Von-Neumann computing
Memristors are a promising building block to the next generation of computing systems. Since 2008, when the physical implementation of a memristor was first postulated, the scientific community has shown a growing interest in this emerging technology. Thus, many other memristive devices have been studied, exploring a large variety of materials and properties. Furthermore, in order to support the design of prac-tical applications, models in different abstract levels have been developed. In fact, a substantial effort has been devoted to the development of memristive based applications, which includes high-density nonvolatile memories, digital and analog circuits, as well as bio-inspired computing. In this context, this paper presents a survey, in hopes of summarizing the highlights of the literature in the last decade
Design and development of an embedded flash memory integrated simulator for the automotive microcontroller firmware validation
Applicazioni automotive possono compromettere la sicurezza delle persone pertanto i componenti devono essere affidabili in qualsiasi condizione operativa. L'affidabilità può essere raggiunta testando i dispositivi dopo la produzione, progettare il test è un compito delicato in quanto non sono presenti fisicamente i primi prototipi del dispositivo. Realizziamo un simulatore di memorie flash integrate di un microcontrollore automotive per facilitare la progettazione dei tes
Reliability of HfO2-Based Ferroelectric FETs: A Critical Review of Current and Future Challenges
Ferroelectric transistors (FeFETs) based on doped
hafnium oxide (HfO2) have received much attention due to
their technological potential in terms of scalability, highspeed,
and low-power operation. Unfortunately, however,
HfO2-FeFETs also suffer from persistent reliability challenges,
specifically affecting retention, endurance, and variability. A
deep understanding of the reliability physics of HfO2-FeFETs is
an essential prerequisite for the successful commercialization
of this promising technology. In this article, we review the
literature about the relevant reliability aspects of HfO2-FeFETs.
We initially focus on the reliability physics of ferroelectric
capacitors, as a prelude to a comprehensive analysis of FeFET
reliability. Then, we interpret key reliability metrics of the FeFET
at the device level (i.e., retention, endurance, and variability)
based on the physical mechanisms previously identified.
Finally, we discuss the implications of device-level reliability
metrics at both the circuit and system levels. Our integrative
approach connects apparently unrelated reliability issues and
suggests mitigation strategies at the device, circuit, or system
level. We conclude this article by proposing a set of research
opportunities to guide future development in this field
- …