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In this paper, we present an efficient hardware mapping methodology for realizing vector matrix multiplication (VMM) on resistive memory (RRAM) arrays. Using the proposed VMM computation technique, we experimentally demonstrate a…

Emerging Technologies · Computer Science 2020-06-11 Sandeep Kaur Kingra , Vivek Parmar , Shubham Negi , Sufyan Khan , Boris Hudec , Tuo-Hung Hou , Manan Suri

Increased process variability and reliability issues present a major challenge for future SRAM trends. Non-intrusive and accurate SRAM stability measurement is crucial for estimating yield in large SRAM arrays. Conventional SRAM variability…

Hardware Architecture · Computer Science 2024-11-26 Bartomeu Alorda , Cristian Carmona , Gabriel Torrens , Sebastia Bota

Superconductor electronics (SCE) is a promising complementary and beyond CMOS technology. However, despite its practical benefits, the realization of SCE logic faces a significant challenge due to the absence of dense and scalable…

Superconductivity · Physics 2024-12-05 Mustafa Altay Karamuftuoglu , Beyza Zeynep Ucpinar , Sasan Razmkhah , Massoud Pedram

3-D cross point phase change memory (PCM) is a promising emerging memory. However, dynamic performances of 3-D cross point PCM are limited and the role of bias scheme is unknown. Previous studies on bias schemes for planar memories use…

Emerging Technologies · Computer Science 2019-06-06 Yu Lei , Meng Liu , Houpeng Chen , Xi Li , Qian Wang , Zhitang Song

Memory accounts for a considerable portion of the total power budget and area of digital systems. Furthermore, it is typically the performance bottleneck of the processing units. Therefore, it is critical to optimize the memory with respect…

Hardware Architecture · Computer Science 2019-02-04 Ghasem Pasandi , Raghav Mehta , Massoud Pedram , Shahin Nazarian

3D NAND flash memory with advanced multi-level cell techniques provides high storage density, but suffers from significant performance degradation due to a large number of read-retry operations. Although the read-retry mechanism is…

Hardware Architecture · Computer Science 2021-04-21 Jisung Park , Myungsuk Kim , Myoungjun Chun , Lois Orosa , Jihong Kim , Onur Mutlu

Analog in-memory computing (AIMC) accelerators enable efficient deep neural network computation directly within memory using resistive crossbar arrays, where model parameters are represented by the conductance states of memristive devices.…

Machine Learning · Computer Science 2025-10-06 Jindan Li , Zhaoxian Wu , Gaowen Liu , Tayfun Gokmen , Tianyi Chen

We propose an improved scheme for low-power writing of binary bits in non-volatile (multiferroic) magnetic memory with electrically generated mechanical stress. Compared to an earlier idea [Tiercelin, et al., J. Appl. Phys., 109, 07D726…

Mesoscale and Nanoscale Physics · Physics 2015-06-18 Ayan K. Biswas , Supriyo Bandyopadhyay , Jayasimha Atulasimha

There have been a plethora of research on multi-level memory devices, where the resistive random-access memory (RRAM) is a prominent example. Although it is easy to write an RRAM device into multiple (even quasi-continuous) states, it…

Emerging Technologies · Computer Science 2024-10-29 Yongxiang Li , Shiqing Wang , Zhong Sun

Magnetic random-access memory (MRAM) is a promising memory technology due to its high density, non-volatility, and high endurance. However, achieving high memory fidelity incurs significant write-energy costs, which should be reduced for…

Information Theory · Computer Science 2020-09-22 Yongjune Kim , Yoocharn Jeon , Cyril Guyot , Yuval Cassuto

A non-volatile SRAM cell is proposed for low power applications using Spin Transfer Torque-Magnetic Tunnel Junction (STT-MTJ) devices. This novel cell offers non-volatile storage, thus allowing selected blocks of SRAM to be switched off…

Hardware Architecture · Computer Science 2019-10-11 Kanika Monga , Akul Malhotra , Nitin Chaturvedi , S. Gurunayaranan

The memory demands of large-scale deep neural networks (DNNs) require synaptic weight values to be stored and updated in off-chip memory like dynamic random-access memory, which reduces energy efficiency and increases training time.…

Applied Physics · Physics 2025-10-08 Abhishek Kumar , Peter D. Hodgson , Manus Hayne , Avirup Dasgupta

In energy-constrained scenarios such as IoT applications, the primary requirement for System-on-Chips (SoCs) is to increase battery life. However, when performing sub/near-threshold operations, the relatively large leakage current hinders…

Hardware Architecture · Computer Science 2024-04-09 Shan Shen , Hao Xu , Yongliang Zhou , Ming Ling , Wenjian Yu

Serial connection of multiple memory cells using perpendicular magnetic tunnel junctions (pMTJ) is proposed as a way to increase magnetic random access memory (MRAM) storage density. Multi-bit storage element is designed using pMTJs…

Applied Physics · Physics 2019-07-24 Piotr Rzeszut , Witold Skowroński , Sławomir Ziętek , Jerzy Wrona , Tomasz Stobiecki

Sub/Near-threshold static random-access memory (SRAM) design is crucial for addressing the memory bottleneck in energy-constrained applications. However, the high integration density and reliability under process variations demand an…

Hardware Architecture · Computer Science 2022-02-25 Shan Shen , Peng Cao , Ming Ling , Longxing Shi

Non-volatile memory, such as resistive RAM (RRAM), is an emerging energy-efficient storage, especially for low-power machine learning models on the edge. It is reported, however, that the bit error rate of RRAMs can be up to 3.3% in the…

A primary source of increased read time on NAND flash comes from the fact that in the presence of noise, the flash medium must be read several times using different read threshold voltages for the decoder to succeed. This paper proposes an…

Information Theory · Computer Science 2022-02-14 Borja Peleato , Rajiv Agarwal , John Cioffi , Minghai Qin , Paul H. Siegel

Compute in-memory (CIM) is a promising technique that minimizes data transport, the primary performance bottleneck and energy cost of most data intensive applications. This has found wide-spread adoption in accelerating neural networks for…

Signal Processing · Electrical Eng. & Systems 2021-02-16 Brian Crafton , Samuel Spetalnick , Arijit Raychowdhury

3D NAND flash memory with advanced multi-level cell techniques provides high storage density, but suffers from significant performance degradation due to a large number of read-retry operations. Although the read-retry mechanism is…

Hardware Architecture · Computer Science 2021-03-15 Jisung Park , Myungsuk Kim , Myoungjun Chun , Lois Orosa , Jihong Kim , Onur Mutlu

The SRAM cell is made up of latch, which ensures that the cell data is preserved as long as power is turned on and refresh operation is not required for the SRAM cell. SRAM is widely used for on-chip cache memory in microprocessors, game…

Hardware Architecture · Computer Science 2019-05-22 Apollos Ezeogu