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.

该创新合作伙伴关系 - 研究合作伙伴关系 (PFI-RP) 项目更广泛的影响/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出现，并从根本上改变了计算、网络和数据存储行业。 然而，现有硬件无法支撑以数据为中心的计算的快速增长。 特别是，快速且节能的人工智能需要更好的嵌入式存储技术（即计算机芯片内的数据存储设备），这些技术必须同时快速读取和写入，同时以低成本和低功耗提供高容量。该项目将通过开发一种新型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 因其低功耗和高耐用性而成为新兴人工智能系统的主要竞争者，经过十多年的研发，正在进入半导体行业的批量生产。 然而，其当前版本受到密度和速度限制，限制了其最终的潜在市场。该项目将开发基于新物理原理和材料的设备和存储器阵列，这将使设备能够克服现有 MRAM 的物理限制，并实现更高的速度，并更好地扩展到更小的位尺寸。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点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