Functionality Enhanced Memories for Edge-AI Embedded Systems

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Organic electrochemical transistors are emerging as prominent biochemical sensors for multi-sensing, including ions, metabolites, hormones, or viruses. However, the implementation of the devices is mainly limited to a single-analyte detection and a single- ...

A frequency scaling governor is critical for the performance management of cloud servers, as it enhances energy efficiency and helps to control operational temperatures, thereby ensuring system reliability. However, our in-depth analysis of the application ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

In the past decades, a significant increase of the transistor density on a chip has led to exponential growth in computational power driven by Moore's law. To overcome the bottleneck of traditional von-Neumann architecture in computational efficiency, effo ...

Field-effect transistors (FETs) based on two-dimensional materials (2DMs) with atomically thin channels have emerged as a promising platform for beyond-silicon electronics. However, low carrier mobility in 2DM transistors driven by phonon scattering remain ...

The versatility of half-bridge configuration of silicon carbide (SiC) metal-oxide-semiconductor field-effect transistor (MOSFET) power module contributes to its widespread adoption, highlighting the popularity and significance of its corresponding dual gat ...

The engineering of tin halide perovskites has led to the development of p-type transistors with field-effect mobilities of over 70 cm2 V-1 s-1. However, due to their background hole doping, these perovskites are not suitable for n-type transistors. Ambipol ...

Safety learning allows the identification of non-threatening situations, a learning process instrumental for survival and psychic health. In contrast to fear learning, in which a sensory cue (conditioned stimulus, CS) is temporally linked to a mildly avers ...

New particle formation (NPF) substantially contributes to global cloud condensation nuclei (CCN), and their climate impacts. Individual NPF events are also thought to increase local CCN, cloud droplet number (CDN), and cloud albedo. High resolution simulat ...

Shared Virtual Memory (SVM) is a mechanism that allows host-side applications and FPGA accelerators to access the same virtual address space. It enables accelerating algorithms with unpredictable memory access patterns by making transparent pointer sharing ...

The scientific progress is significantly transforming contemporary society with the introduction and widespread application of technologies like artificial intelligence and quantum computing. Despite their profound impact, these technologies necessitate en ...

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

The digital revolution has significantly transformed our world over the past decades, driven by the scaling of transistor dimensions and the exponential increase in computation power. However, as the CMOS scaling era approaches its end, the semiconductor i ...

Modern hardware is increasingly complex, requiring increasing effort to understand in order to carefully engineer systems for optimal performance and effective utilization. Moreover, established design principles and assumptions are not portable to modern ...

Organic electrochemical transistors (OECTs) have gained enormous attention due to their potential for bioelectronics and neuromorphic computing. However, their implementation into real-world applications is still impeded by a lack of understanding of the c ...

Defects in solids are unavoidable and can create complex electronic states that can significantly influence the electrical and optical properties of semiconductors. With the rapid progress in the integration of 2D semiconductors in practical devices, it is ...

Selective area epitaxy is a promising approach to definenanowirenetworks for topological quantum computing. However, it is challengingto concurrently engineer nanowire morphology, for carrier confinement,and precision doping, to tune carrier density. We re ...

How the 'what', 'where', and 'when' of past experiences are stored in episodic memories and retrieved for suitable decisions remains unclear. In an effort to address these questions, the authors present computational models of neural networks that behave l ...

Functionality Enhanced Memories for Edge-AI Embedded Systems

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