Results 21 to 30 of about 401 (157)

Design and Analysis of an Ultra-Dense, Low-Leakage, and Fast FeFET-Based Random Access Memory Array

IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2019
High static power associated with static random access memory (SRAM) represents a bottleneck in increasing the amount of on-chip memory. Novel, emerging nonvolatile memories such as spintransfer torque magnetic random access memory (STT-RAM), resistive ...
Dayane Reis, Kai Ni, Wriddhi Chakraborty, Xunzhao Yin, Martin Trentzsch, Stefan Dunkel, Thomas Melde, Johannes Muller, Sven Beyer, Suman Datta, Michael T. Niemier, Xiaobo Sharon Hu   +11 more
doaj   +1 more source

HOPE: Holistic STT-RAM Architecture Exploration Framework for Future Cross-Platform Analysis

IEEE Access
Spin Transfer Torque Random Access Memory (STT-RAM) is an emerging Non-Volatile Memory (NVM) technology that has garnered attention to overcome the drawbacks of conventional CMOS-based technologies.
Saeed Seyedfaraji, Markus Bichl, Asad Aftab, Semeen Rehman   +3 more
doaj   +1 more source

Dual referenced composite free layer design optimization for improving switching efficiency of spin-transfer torque RAM

AIP Advances, 2017
We present a detailed numerical analysis of switching efficiency for the recently proposed dual referenced composite free layer structure with respect to Gilbert damping. Low anisotropy assistive layers enable reduction of Gilbert damping and an increase
Roy Bell, Jiaxi Hu, R. H. Victora
doaj   +1 more source

Multi-Port 1R1W Transpose Magnetic Random Access Memory by Hierarchical Bit-Line Switching

IEEE Access, 2019
Emerging Magnetic Random-Access Memory (MRAM) has shown a great potential to replace Static-RAM (SRAM) and Dynamic-RAM (DRAM) in the working memories including Cache and main memory. MRAM benefits from its high-density, fast speed, low standby power, and
Liang Chang, Zhaohao Wang, Youguang Zhang, Weisheng Zhao   +3 more
doaj   +1 more source

STT-RAM-Based Hierarchical in-Memory Computing

IEEE Transactions on Parallel and Distributed Systems
In-memory computing promises to overcome the von Neumann bottleneck in computer systems by performing computations directly within the memory. Previous research has suggested using Spin-Transfer Torque RAM (STT-RAM) for in-memory computing due to its non-volatility, low leakage power, high density, endurance, and commercial viability.
Dhruv Gajaria, Kevin Antony Gomez, Tosiron Adegbija   +2 more
openaire   +2 more sources

Leveraging MLC STT-RAM for energy-efficient CNN training [PDF]

Proceedings of the International Symposium on Memory Systems, 2018
Graphics Processing Units (GPUs) are extensively used in training of convolutional neural networks (CNNs) due to their promising compute capability. However, GPU memory capacity, bandwidth, and energy are becoming critical system bottlenecks with increasingly larger and deeper training models.
Hengyu Zhao, Jishen Zhao
openaire   +1 more source

TTEC: Data Allocation Optimization for Morphable Scratchpad Memory in Embedded Systems

IEEE Access, 2018
Scratchpad memory (SPM) is widely utilized in many embedded systems as a software-controlled on-chip memory to replace the traditional cache. New non-volatile memory (NVM) has emerged as a promising candidate to replace SRAM in SPM, due to its ...
Linbo Long, Qing Ai, Xiaotong Cui, Jun Liu   +3 more
doaj   +1 more source

People Counting and Positioning Using Low‐Resolution Infrared Images for FeFET‐Based In‐Memory Computing

Advanced Electronic Materials, EarlyView.
In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar, Li Zhang, Alexander Rehmer, Marc Lupp, Subhashree Baskaran, Osama Abdelaal, Franz Müller, Nandakishor Yadav, Bing Li, Thomas Kämpfe   +9 more
wiley   +1 more source

Low Power Design for Future Wearable and Implantable Devices

Journal of Low Power Electronics and Applications, 2016
With the fast progress in miniaturization of sensors and advances in micromachinery systems, a gate has been opened to the researchers to develop extremely small wearable/implantable microsystems for different applications.
Katrine Lundager, Behzad Zeinali, Mohammad Tohidi, Jens K. Madsen, Farshad Moradi   +4 more
doaj   +1 more source

Silicon Nitride Resistive Memories

Advanced Electronic Materials, EarlyView.
Amorphous SiNx is an attractive resistance switching material for ReRAM applications due to its physicochemical properties, such as humidity resistance, low oxygen diffusivity, and is used as a metal diffusion blocker. By modifying the ratio between N and Si atoms, the microstructure of the SiNx is affected, rendering it possible to change the ...
Alexandros‐Eleftherios Mavropoulis, Nikolaos Vasileiadis, Iosif‐Angelos Fyrigos, Emmanouil Stavroulakis, Caroline Bonafos, Pascal Normand, Georgios Ch. Sirakoulis, Panagiotis Dimitrakis   +7 more
wiley   +1 more source