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The use of 1-bit analog-to-digital converters (ADCs) is seen as a promising approach to significantly reduce the power consumption and hardware cost of multiple-input multiple-output (MIMO) receivers. However, the nonlinear distortion due…

Information Theory · Computer Science 2022-10-12 Neil Irwin Bernardo , Jingge Zhu , Yonina C. Eldar , Jamie Evans

Thin-film transistors based on amorphous oxide semiconductors (AOS) are promising candidates for enabling further DRAM scaling and 3D integration, which are critical for advanced computing. Despite extensive research, the charge transport…

Scalability and performance of current flash memories can be improved substantially by replacing the floating poly-Si gate by a layer of Si dots. This multi-dot layer can be fabricated CMOS-compatibly in very thin gate oxide by ion beam…

This work demonstrates a large area process for atomically thin 2D semiconductors to unlock the technological upscale required for their commercial uptake. The new atomic layer deposition (ALD) and conversion technique yields large area…

Dynamic 3D Gaussian splatting (3DGS) extends static 3DGS to render dynamic scenes, enabling AR/VR applications with moving objects. However, implementing dynamic 3DGS on edge devices faces challenges: (1) Loading all Gaussian parameters…

Scalable, high-speed, small-footprint photonic switching platforms are essential for advancing optical communication. An effective optical switch must operate at high duty cycles with fast recovery times, while maintaining substantial…

Aside from recent advances in artificial intelligence (AI) models, specialized AI hardware is crucial to address large volumes of unstructured and dynamic data. Hardware-based AI, built on conventional complementary metal-oxidesemiconductor…

The Quantum Diamond Microscope (QDM) is an emerging magnetic imaging tool enabling noninvasive characterization of electronic circuits through spatially mapping current densities. In this work, we demonstrate wafer-level current sensing of…

Scaling transistors' dimensions has been the thrust for the semiconductor industry in the last 4 decades. However, scaling channel lengths beyond 10 nm has become exceptionally challenging due to the direct tunneling between source and…

Mesoscale and Nanoscale Physics · Physics 2016-08-30 Hesameddin Ilatikhameneh , Tarek Ameen , Bozidar Novakovic , Yaohua Tan , Gerhard Klimeck , Rajib Rahman

While memory-augmented neural networks (MANNs) offer an effective solution for few-shot learning (FSL) by integrating deep neural networks with external memory, the capacity requirements and energy overhead of data movement become enormous…

Hardware Architecture · Computer Science 2024-09-13 Hao-Wei Chiang , Chi-Tse Huang , Hsiang-Yun Cheng , Po-Hao Tseng , Ming-Hsiu Lee , An-Yeu , Wu

We have modified a commercial NOR flash memory array to enable high-precision tuning of individual floating-gate cells for analog computing applications. The modified array area per cell in a 180 nm process is about 1.5 um^2. While this…

Emerging Technologies · Computer Science 2016-10-10 F. Merrikh Bayat , X. Guo , H. A. Ommani , N. Do , K. K. Likharev , D. B. Strukov

For the past four decades, cost and features have driven CMOS scaling. Severe lithography and material limitations seen below the 20 nm node, however, are challenging the fundamental premise of affordable CMOS scaling. Just continuing to…

Emerging Technologies · Computer Science 2015-09-04 Kaushik Vaidyanathan

Content Addressable Memories (CAMs) are considered a key-enabler for in-memory computing (IMC). IMC shows order of magnitude improvement in energy efficiency and throughput compared to traditional computing techniques. Recently, analog CAMs…

Hardware Architecture · Computer Science 2022-03-07 Jinane Bazzi , Jana Sweidan , Mohammed E. Fouda , Rouwaida Kanj , Ahmed M. Eltawil

Orthogonal time frequency space (OTFS) modulation offers superior robustness to high-mobility channels compared to conventional orthogonal frequency-division multiplexing (OFDM) waveforms. However, its explicit delay-Doppler (DD) domain…

Signal Processing · Electrical Eng. & Systems 2026-04-03 Junyao Zheng , Chung-Hsuan Tung , Yuncheng Yao , Nishant Mehrotra , Sandesh Mattu , Zhenzhou Qi , Danyang Zhuo , Robert Calderbank , Tingjun Chen

Analog Content Addressable Memories (aCAMs) have proven useful for associative in-memory computing applications like Decision Trees, Finite State Machines, and Hyper-dimensional Computing. While non-volatile implementations using FeFETs and…

Emerging Technologies · Computer Science 2024-10-15 Paul-Philipp Manea , Nathan Leroux , Emre Neftci , John Paul Strachan

High performance InGaAs gate-all-around (GAA) nanowire MOSFETs with channel length (Lch) down to 20nm have been fabricated by integrating a higher-k LaAlO3-based gate stack with an equivalent oxide thickness of 1.2nm. It is found that…

Mesoscale and Nanoscale Physics · Physics 2015-06-15 Jiangjiang J. Gu , Xinwei Wang , Heng Wu , Roy G. Gordon , Peide D. Ye

Two-dimensional (2D) semiconductors have been suggested both for ultimately-scaled field-effect transistors (FETs) and More-than-Moore nanoelectronics. However, these targets can not be reached without accompanying gate insulators which are…

Charge-trap memory with high-\k dielectric materials is considered to be a promising candidate for next-generation memory devices. Ultrathin layered two-dimensional (2D) materials like graphene and MoS2 have been receiving much attention…

Materials Science · Physics 2014-07-29 Enze Zhang , Weiyi Wang , Cheng Zhang , Yibo Jin , Guodong Zhu , Qingqing Sun , David Wei Zhan , Peng Zhou , Faxian Xiu

In contemporary general-purpose graphics processing units (GPGPUs), the continued increase in raw arithmetic throughput is constrained by the capabilities of the register file (single-cycle) and last-level cache (high bandwidth), which…

Emerging Technologies · Computer Science 2025-07-01 Faaiq Waqar , Ming-Yen Lee , Seongwon Yoon , Seongkwang Lim , Shimeng Yu

Synaptic devices with linear high-speed switching can accelerate learning in artificial neural networks (ANNs) embodied in hardware. Conventional resistive memories however suffer from high write noise and asymmetric conductance tuning,…