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Related papers: Valley-Coupled-Spintronic Non-Volatile Memories wi…

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Processing-in-memory (PIM) turns out to be a promising solution to breakthrough the memory wall and the power wall. While prior PIM designs yield successful implementation of bitwise Boolean logic operations locally in memory, it is…

Hardware Architecture · Computer Science 2018-09-25 Xin Ma , Liang Chang , Shuangchen Li , Lei Deng , Yufei Ding , Yuan Xie

In Valence Change Memory (VCM) cells, the conductance of an insulating switching layer is reversibly modulated by creating and redistributing point defects under an external field. Accurate simulations of the switching dynamics of these…

Disordered Systems and Neural Networks · Physics 2023-01-02 Manasa Kaniselvan , Mathieu Luisier , Marko Mladenović

In-Memory Acceleration (IMA) promises major efficiency improvements in deep neural network (DNN) inference, but challenges remain in the integration of IMA within a digital system. We propose a heterogeneous architecture coupling 8 RISC-V…

Hardware Architecture · Computer Science 2021-09-06 Gianmarco Ottavi , Geethan Karunaratne , Francesco Conti , Irem Boybat , Luca Benini , Davide Rossi

A time-domain analog weighted-sum calculation model is proposed based on an integrate-and-fire-type spiking neuron model. The proposed calculation model is applied to multi-layer feedforward networks, in which weighted summations with…

Emerging Technologies · Computer Science 2018-10-17 Quan Wang , Hakaru Tamukoh , Takashi Morie

The combination of semiconducting properties and synthetically tunable chirality in chiral metal halide semiconductors (CMHS) offer a compelling platform for room temperature control over electronic spin properties, leveraging effects such…

A prototype of magnetoresistive random access memory (MRAM) based on magnetic tunnel junctions (MTJ) was fabricated with crossed-anisotropy of magnetic layers on either side of the tunnelling barrier layer. It is demonstrated that the…

Materials Science · Physics 2007-05-23 A. N. Grigorenko , D. J. Mapps

To usher in the next round of client AI innovation, there is an urgent need to enable efficient, lossless inference of high-accuracy large language models (LLMs) and vision language models (VLMs), jointly referred to as xLMs, on client…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-30 Aditya Ukarande , Deep Shekhar , Marc Blackstein , Ram Rangan

The scaling of the already-matured CMOS technology is steadily approaching its physical limit, motivating the quest for a suitable alternative. Cryogenic operation offers a promising pathway towards continued improvement in computing speed…

Emerging Technologies · Computer Science 2022-04-08 Shamiul Alam , Md Mazharul Islam , Md Shafayat Hossain , Akhilesh Jaiswal , Ahmedullah Aziz

In the last decade, a 2-terminal passive circuit element called a memristor has been developed for non-volatile resistive random access memory and has more recently shown promise for neuromorphic computing. Compared to flash memory,…

Two-dimensional van der Waals (vdW) magnetic materials hold promise for the development of high-density, energy-efficient spintronic devices for memory and computation. Recent breakthroughs in material discoveries and spin-orbit torque…

Applied Physics · Physics 2024-03-25 Shivam N. Kajale , Thanh Nguyen , Mingda Li , Deblina Sarkar

Non-volatile flip-flops (NVFFs) using power gating techniques promise to overcome the soaring leakage power consumption issue with the scaling of CMOS technology. Magnetic tunnel junction (MTJ) is a good candidate for constructing the NVFF…

Emerging Technologies · Computer Science 2020-07-15 Ziyi Wang , Zhaohao Wang , Yansong Xu , Bi Wu , Weisheng Zhao

Compute-in-memory (CiM) is a promising approach to alleviating the memory wall problem for domain-specific applications. Compared to current-domain CiM solutions, charge-domain CiM shows the opportunity for higher energy efficiency and…

Emerging Technologies · Computer Science 2021-02-03 Guodong Yin , Yi Cai , Juejian Wu , Zhengyang Duan , Zhenhua Zhu , Yongpan Liu , Yu Wang , Huazhong Yang , Xueqing Li

DRAM-based main memory and its associated components increasingly account for a significant portion of application performance bottlenecks and power budget demands inside the computing ecosystem. To alleviate the problems of storage density…

Cryptography and Security · Computer Science 2019-02-12 Fan Yao , Guru Venkataramani

Valleytronics is rapidly emerging as an exciting area of basic and applied research. In two dimensional systems, valley polarisation can dramatically modify physical properties through electron-electron interactions as demonstrated by such…

We demonstrate non-volatile optical functionality by embedding multi-layer $HfO_2/Al_2O_3$ memristors with III-V/Si photonics. The wafer-bonded III-V/Si memristor facilitates non-volatile optical functionality for a variety of devices such…

Non-volatile memory (NVM) technologies are interesting alternatives for building the on-chip Last-Level Cache (LLC). Their advantages, compared to SRAM memory, are higher density and lower static power, but each write operation slightly…

Hardware Architecture · Computer Science 2022-04-08 Carlos Escuin , Pablo Ibañez , Teresa Monreal , Jose M. Llaberia , Victor Viñals

The demands of modern electronic components require advanced computing platforms for efficient information processing to realize in-memory operations with a high density of data storage capabilities towards developing alternatives to von…

The ramp reversal memory (RRM) is a non-volatile memory effect previously observed in correlated oxides exhibiting temperature-driven metal-insulator transitions (MITs). In essence, when a system displaying RRM is heated to a specific…

Strongly Correlated Electrons · Physics 2025-07-08 Avital Fried , Ouriel Gotesdyner , Irena Feldman , Amit Kanigel , Amos Sharoni

Voltage control of magnetic anisotropy (VCMA) induced by charge accumulation is typically considered as an ultrafast process, enabling energy-efficient and high-speed magnetization switching in spintronic devices. In this work, we…

The deployment of Large Language Models (LLMs) on edge devices is fundamentally constrained by the "Memory Wall" the bottleneck where data movement latency outstrips arithmetic throughput. Standard inference runtimes often incur significant…

Computation and Language · Computer Science 2026-01-08 Bugra Kilictas , Faruk Alpay