PFI-RP: Partnership to develop next-generation memory chips for intelligent computing systems.

PFI-RP：合作开发用于智能计算系统的下一代存储芯片。

• 批准号: 1919109
• 负责人: Pedram Khalili Amiri
• 金额: $ 55万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1919109&HistoricalAwards=false
• 关键词: PFI; RP; Partnership; develop; next

The broader impact/commercial potential of this Partnerships for Innovation - Research Partnerships (PFI-RP) project is in providing a new hardware platform for energy-efficient and high-performance computing systems. The rise of big data has enabled the emergence of artificial intelligence (AI) in the cloud and on edge devices, and is fundamentally transforming the computing, networking and data storage industries. However, existing hardware cannot sustain the rapid growth of data-centric computing. In particular, fast and energy-efficient AI requires better embedded memory technologies (i.e. data storage devices inside computer chips) that are simultaneously fast to read and write, while delivering high capacities with low cost, along with low power consumption. This project will address this challenge by developing a novel type of on-chip magnetic memory device, focusing on its commercialization in the data storage, AI, communications and networking markets. The proposed project will develop a new type of magnetic random access memory (MRAM), referred to as voltage-controlled spin-orbit (VCSO) memory. MRAM is the leading contender for emerging AI systems due to its low power consumption and high endurance, and is entering volume manufacturing across the semiconductor industry after more than a decade of research and development. However, its current version suffers from density and speed limitations that limit its ultimate addressable market. This project will develop devices and memory arrays based on new physical principles and materials, which will allow the devices to overcome the physical limitations of existing MRAM, and achieve higher speeds with better scalability to smaller bit dimensions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该创新研究伙伴关系（PFI-RP）项目的更广泛影响/商业潜力在于为节能和高性能计算系统提供新的硬件平台。 大数据的兴起使得人工智能（AI）在云端和边缘设备上的出现成为可能，并从根本上改变了计算、网络和数据存储行业。 然而，现有的硬件无法维持以数据为中心的计算的快速增长。 特别是，快速和节能的人工智能需要更好的嵌入式存储器技术（即计算机芯片内的数据存储设备），这些技术可以同时快速读取和写入，同时以低成本提供高容量，沿着低功耗。该项目将通过开发一种新型的片上磁存储器件来应对这一挑战，重点关注其在数据存储、人工智能、通信和网络市场的商业化。拟议的项目将开发一种新型的磁性随机存取存储器（MRAM），称为压控自旋轨道（VCSO）存储器。 MRAM因其低功耗和高耐久性而成为新兴AI系统的领先竞争者，并在经过十多年的研究和开发后进入半导体行业的批量生产。 然而，它目前的版本受到密度和速度的限制，限制了其最终的可寻址市场。该项目将开发基于新的物理原理和材料的器件和存储器阵列，这将使器件能够克服现有MRAM的物理限制，并实现更高的速度和更好的可扩展性，以更小的位尺寸。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Reconfigurable Physically Unclonable Functions Based on Nanoscale Voltage‐Controlled Magnetic Tunnel Junctions

• DOI: 10.1002/aelm.202300195
• 发表时间: 2023-06
• 期刊: Advanced Electronic Materials
• 影响因子: 6.2
• 作者: Yixin Shao;N. Dávila;F. Ebrahimi;J. Katine;G. Finocchio;P. Khalili Amiri

Sub-volt switching of nanoscale voltage-controlled perpendicular magnetic tunnel junctions

• DOI: 10.1038/s43246-022-00310-x
• 发表时间: 2022-11-14
• 期刊: COMMUNICATIONS MATERIALS
• 影响因子: 7.8
• 作者: Shao, Yixin;Lopez-Dominguez, Victor;Amiri, Pedram Khalili
• 通讯作者: Amiri, Pedram Khalili

Probabilistic computing with voltage-controlled dynamics in magnetic tunnel junctions

磁隧道结中压控动力学的概率计算

• DOI: 10.1088/1361-6528/acf6c7
• 发表时间: 2023
• 期刊: Nanotechnology
• 影响因子: 3.5
• 作者: Shao, Yixin;Duffee, Christian;Raimondo, Eleonora;Davila, Noraica;Lopez-Dominguez, Victor;Katine, Jordan A;Finocchio, Giovanni;Khalili Amiri, Pedram
• 通讯作者: Khalili Amiri, Pedram

Implementation of Artificial Neural Networks Using Magnetoresistive Random-Access Memory-Based Stochastic Computing Units

使用基于磁阻随机存取存储器的随机计算单元实现人工神经网络

• DOI: 10.1109/lmag.2021.3071084
• 发表时间: 2021
• 期刊: IEEE Magnetics Letters
• 影响因子: 1.2
• 作者: Shao, Yixin;Sinaga, Sisilia Lamsari;Sunmola, Idris O.;Borland, Andrew S.;Carey, Matthew J.;Katine, Jordan A.;Lopez-Dominguez, Victor;Amiri, Pedram Khalili
• 通讯作者: Amiri, Pedram Khalili

First-principles calculation of the Dzyaloshinskii-Moriya interaction: A Green's function approach

• DOI: 10.1103/physrevb.103.094410
• 发表时间: 2021-03-05
• 期刊: PHYSICAL REVIEW B
• 影响因子: 3.7
• 作者: Mahfouzi, Farzad;Kioussis, Nicholas
• 通讯作者: Kioussis, Nicholas