相关论文: Scaling Analysis of Nanowire Phase Change Memory
The paper presents a straightforward modelling approach to compute the power loss distribution in GaN HEMT based three phase and three level (3L) active neutral point clamped (ANPC) inverters, for different pulse width modulated techniques.…
Convolutional Neural Networks have dramatically improved in recent years, surpassing human accuracy on certain problems and performance exceeding that of traditional computer vision algorithms. While the compute pattern in itself is…
Memory dephasing and its impact on the rate of entanglement generation in quantum repeaters is addressed. For systems that rely on probabilistic schemes for entanglement distribution and connection, we estimate the maximum achievable rate…
Traditional DRAM-based main memory systems face several challenges with memory refresh overhead, high latency, and low throughput as the industry moves towards smaller DRAM cells. These issues have been exacerbated by the emergence of…
After more than 30 years of validation of Moore's law, the CMOS technology has already entered the nanoscale (sub-100nm) regime and faces strong limitations. The nanowire transistor is one candidate which has the potential to overcome the…
Superscaling properties of 12C, 16O and 40Ca nuclear responses, induced by electron and neutrino scattering, are studied for momentum transfer values between 300 and 700 MeV/c. We have defined two indexes to have quantitative estimates of…
Acquiring quantitative information on charge transfer (CT) dynamics at the nanoscale remains an important scientific challenge. In particular, CT processes in single molecules at surfaces needs to be investigated to be properly controlled…
As the demand for high-performance microprocessors increases, the circuit complexity and the rate of data transfer increases resulting in higher power consumption. We propose a clocking architecture that uses a series LC resonance and…
The rapid growth of deep neural network (DNN) workloads has significantly increased the demand for large-capacity on-chip SRAM in machine learning (ML) applications, with SRAM arrays now occupying a substantial fraction of the total die…
The concept of scalability analysis of numerical parallel applications has been revisited, with the specific goals defined for the performance estimation of research applications. A series of Community Climate Model System (CCSM) numerical…
We have measured the critical phase change conditions induced by electrical pulses in Ge2Sb2Te5 nanopillar phase change memory devices by constructing a comprehensive resistance map as a function of pulse parameters (width, amplitude and…
Increasingly complex neural network architectures have achieved phenomenal performance. However, these complex models require massive computational resources that consume substantial amounts of electricity, which highlights the potential…
Neuromorphic photonics promises sub-nanosecond latency, ultrawide bandwidth, and high parallelism, but practical scalability is constrained by fabrication tolerances, spectral alignment, and tuning energy. Here, we present a large-scale,…
Light trapping in sub-wavelength semiconductor nanowires (NWs) offers a promising approach to simultaneously reducing material consumption and enhancing photovoltaic performance. Nevertheless, the absorption efficiency of a NW, defined by…
It is now widely accepted that the CMOS technology implementing irreversible logic will hit a scaling limit beyond 2016, and that the increased power dissipation is a major limiting factor. Reversible computing can potentially require…
In-memory computing is a promising non-von Neumann approach for making energy-efficient deep learning inference hardware. Crossbar arrays of resistive memory devices can be used to encode the network weights and perform efficient analog…
Spin-transfer magnetic random access memory is of significant interest for cryogenic applications where a persistent, fast, low-energy consumption and high device density is needed. Here we report the low-temperature nanosecond duration…
Portable devices like smartphones, tablets, wearable electronic devices, medical implants, wireless sensor nodes, and Internet-of-Things (IoT) devices have tremendous constraints on their energy consumption. Adding more functionalities onto…
It is suggested that low dimensionality can improve the thermoelectric (TE) power factor of a device, offering an enhancement of the ZT figure of merit. In this work the atomistic sp3d5s*-spin-orbit-coupled tight-binding model and the…
Intermolecular charge transfer reactions are key processes in physical chemistry. The electron-transfer rates depend on a few system's parameters, such as temperature, electromagnetic field, distance between adsorbates and, especially, the…