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Spin-Transfer Torque RAM (STTRAM) is a promising alternative to SRAM in on-chip caches due to several advantages. These advantages include non-volatility, low leakage, high integration density, and CMOS compatibility. Prior studies have…

Hardware Architecture · Computer Science 2020-09-25 Kyle Kuan , Tosiron Adegbija

Spin-Transfer Torque Magnetic RAM} (STT-MRAM) is a promising alternative for SRAMs in on-chip cache memories. Besides all its advantages, high error rate in STT-MRAM is a major limiting factor for on-chip cache memories. In this paper, we…

Hardware Architecture · Computer Science 2026-01-05 Elham Cheshmikhani , Hamed Farbeh , Hossein Asadi

Risk Limiting Dispatch (RLD) was proposed recently as a mechanism that utilizes information and market recourse to reduce reserve capacity requirements, emissions and achieve other system operator objectives. It induces a set of simple…

Optimization and Control · Mathematics 2012-12-04 Junjie Qin , Han-I Su , Ram Rajagopal

Microarchitectural attacks are a significant concern, leading to many hardware-based defense proposals. However, different defenses target different classes of attacks, and their impact on each other has not been fully considered. To raise…

Cryptography and Security · Computer Science 2025-04-15 Kartik Ramkrishnan , Antonia Zhai , Stephen McCamant , Pen Chung Yew

In-memory computing is a promising approach to addressing the processor-memory data transfer bottleneck in computing systems. We propose Spin-Transfer Torque Compute-in-Memory (STT-CiM), a design for in-memory computing with Spin-Transfer…

Emerging Technologies · Computer Science 2017-11-22 Shubham Jain , Ashish Ranjan , Kaushik Roy , Anand Raghunathan

Spin-torque transfer magnetic random access memory (STT-MRAM) is a promising emerging non-volatile memory (NVM) technology with wide applications. However, the data recovery of STT-MRAM is affected by the diversity of channel raw bit error…

Information Theory · Computer Science 2024-10-08 Xingwei Zhong , Kui Cai , Peng Kang , Guanghui Song , Bin Dai

Due to increasing cache sizes and large leakage consumption of SRAM device, conventional SRAM caches contribute significantly to the processor power consumption. Recently researchers have used non-volatile memory devices to design caches,…

Hardware Architecture · Computer Science 2014-05-01 Sparsh Mittal

Large Language Model (LLM) inference on edge Neural Processing Units (NPUs) is fundamentally constrained by limited on-chip memory capacity. Although high-density embedded DRAM (eDRAM) is attractive for storing activation workspaces, its…

Hardware Architecture · Computer Science 2026-04-10 Jintao Zhang , Xuanyao Fong

Read disturbance in modern DRAM chips is a widespread phenomenon and is reliably used for breaking memory isolation, a fundamental building block for building robust systems. RowHammer and RowPress are two examples of read disturbance in…

We numerically investigate the effect of magnetic and electrical damages at the edge of a perpendicular magnetic random access memory (MRAM) cell on the spin-transfer-torque (STT) efficiency that is defined by the ratio of thermal stability…

Materials Science · Physics 2015-09-02 Kyungmi Song , Kyung-Jin Lee

Increasing storage density exacerbates DRAM read disturbance, a circuit-level vulnerability exploited by system-level attacks. Unfortunately, existing defenses are either ineffective or prohibitively expensive. Efficient mitigation is…

Cryptography and Security · Computer Science 2024-08-28 Abdullah Giray Yağlıkçı

Spin-Torque-Transfer RAM (STTRAM) is a promising technology however process variation poses serious challenge to sensing. To eliminate bit-to-bit process variation we propose a reference-less, destructive slope detection technique which…

Emerging Technologies · Computer Science 2023-06-08 Seyedhamidreza Motaman , Swaroop Ghosh , Jae-Won Jang , Anirudh Iyengar , Rekha Govindaraj , Zakir Khondker

Quad-level cell (QLC) flash offers significant benefits in cost and capacity, but its limited reliability leads to frequent read retries, which severely degrade read performance. A common strategy in high-density flash storage is to program…

Hardware Architecture · Computer Science 2025-08-28 Yanyun Wang , Dingcui Yu , Yina Lv , Yunpeng Song , Yumiao Zhao , Liang Shi

Machine unlearning for large language models (LLMs) aims to selectively remove memorized content such as private data, copyrighted text, or hazardous knowledge, without costly full retraining. Most existing methods require a retain set of…

Machine Learning · Computer Science 2026-05-11 Zizhao Hu , Ameya Godbole , Johnny Tian-Zheng Wei , Mohammad Rostami , Jesse Thomason , Robin Jia

In recent years, researchers have explored use of non-volatile devices such as STT-RAM (spin torque transfer RAM) for designing on-chip caches, since they provide high density and consume low leakage power. A common limitation of all…

Hardware Architecture · Computer Science 2013-11-01 Sparsh Mittal

As deep neural network (DNN) models are growing exponentially in size, their deployment on resource-constrained edge platforms is becoming increasingly challenging. In-memory-computing (IMC) with non-volatile memories (NVMs) has emerged as…

Emerging Technologies · Computer Science 2026-04-07 Imtiaz Ahmed , Sumeet Kumar Gupta

Much research has shown that applications have variable runtime cache requirements. In the context of the increasingly popular Spin-Transfer Torque RAM (STT-RAM) cache, the retention time, which defines how long the cache can retain a cache…

Hardware Architecture · Computer Science 2019-05-20 Kyle Kuan , Tosiron Adegbija

Spin transfer torque magnetic random access memory (STT-MRAM) is considered as one of the most promising candidates to build up a true universal memory thanks to its fast write/read speed, infinite endurance and non-volatility. However the…

Emerging Technologies · Computer Science 2015-06-04 Weisheng Zhao , Sumanta Chaudhuri , Celso Accoto , Jacques-Olivier Klein , Claude Chappert , Pascale Mazoyer

We present CS-SHRED, a novel deep learning architecture that integrates Compressed Sensing (CS) into a Shallow Recurrent Decoder (SHRED) to reconstruct spatiotemporal dynamics from incomplete, compressed, or corrupted data. Our approach…

Machine Learning · Computer Science 2025-08-01 Romulo B. da Silva , Diego Passos , Cássio M. Oishi , J. Nathan Kutz

A new device structure for spin transfer torque based magnetic random access memory is proposed for on-chip memory applications. Our device structure exploits spin Hall effect to create a differential memory cell that exhibits fast and…

Mesoscale and Nanoscale Physics · Physics 2014-02-12 Yusung Kim , Sri Harsha Choday , Kaushik Roy