PFI-RP: Resilient and Energy-Efficient Memory Chips for Enhanced Mobile AI and Personalized Machine Learning

PFI-RP：用于增强移动人工智能和个性化机器学习的弹性和节能内存芯片

• 批准号: 2345655
• 负责人: Shan Wang
• 金额: $ 100万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-03-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2345655&HistoricalAwards=false
• 关键词: PFI; RP; Resilient; Energy; Efficient

The broader impact of this Partnerships for Innovation - Research Partnerships (PFI-RP) project extends across scientific, technological, and societal realms. By focusing on the development of a resilient, fast-switching, and energy-efficient magnetoresistive random access memory (MRAM), this research aims to revolutionize the landscape of mobile artificial intelligence (AI). Unlike current memory options, this innovation is like a supercharged engine for your smartphone or smartwatch, making them smarter and much longer lasting with just one charge. This means not just faster processing, but also a smaller, personalized AI right in your device. The research tackles thermal challenges, design intricacies and nanofabrication to make this technology work seamlessly, with the goal of creating jobs and preparing students for the future. Think of it as upgrading the brain of your gadgets. Once developed, this AI chip could be used by companies like Apple or Tesla to enable brand-new applications. The demand for this kind of tech is huge and growing, and it could lead to a major breakthrough in how we use AI in our daily lives, while making our devices and privacy securely protected. The project will also empower a diverse group of students with crucial skills for innovation and semiconductor fabrication.The proposed project aims to tackle critical technical hurdles in the development of the next generation of MRAM materials and devices, focusing on enhancing thermal robustness, achieving fast and enduring switching, and ensuring sustainable energy efficiency. With a specific focus on applications in mobile AI, the research seeks innovative solutions that address challenges currently limiting the widespread adoption of MRAM technologies. In the evolving landscape of mobile computing, where AI algorithms promise transformative user experiences, data security and privacy concerns are paramount. Traditional AI models, trained extensively in the cloud, pose risks of compromising personal user information. Moreover, their deployment on mobile devices often results in suboptimal performance for certain user groups. This project will advance the state of the art in mobile AI by leveraging nonvolatile MRAM-based associative memories at the hardware level and embeddings-based neural networks at the software level. By doing so, the research envisions a future where AI applications on mobile devices are not only efficient (preserving battery power) but also secure (keeping private data locally on your own device), ensuring a more inclusive and responsive experience for users of all kinds of AI tools.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.

这一创新伙伴关系-研究伙伴关系（PFI-RP）项目的更广泛影响跨越科学，技术和社会领域。通过专注于弹性，快速切换和节能的磁阻随机存取存储器（MRAM）的发展，这项研究的目的是彻底改变移动的人工智能（AI）的景观。与目前的内存选项不同，这项创新就像是智能手机或智能手表的增压引擎，只需一次充电，就能让它们变得更智能、更持久。这不仅意味着更快的处理速度，还意味着设备中更小的个性化AI。该研究解决了热挑战，设计复杂性和纳米纤维，使这项技术无缝工作，目标是创造就业机会，为学生的未来做好准备。把它想象成升级你的小玩意的大脑。一旦开发出来，这种人工智能芯片可以被苹果或特斯拉等公司用来实现全新的应用。对这种技术的需求是巨大的，而且还在不断增长，它可能会导致我们在日常生活中使用人工智能的方式取得重大突破，同时使我们的设备和隐私得到安全保护。该项目旨在解决下一代MRAM材料和器件开发中的关键技术障碍，重点是增强热鲁棒性，实现快速持久的开关，并确保可持续的能源效率。该研究特别关注移动的AI应用，旨在寻求创新的解决方案，以解决目前限制MRAM技术广泛采用的挑战。在不断发展的移动的计算环境中，人工智能算法有望带来变革性的用户体验，数据安全和隐私问题至关重要。传统的人工智能模型在云端进行了广泛的训练，存在泄露个人用户信息的风险。此外，它们在移动的设备上的部署通常导致某些用户组的次优性能。该项目将通过在硬件层面利用基于非易失性MRAM的关联存储器和在软件层面利用基于嵌入的神经网络来推进移动的AI的最新技术。通过这样做，该研究设想了一个未来，即移动的设备上的人工智能应用不仅高效（保存电池电量），同时还安全可靠（将私人数据保存在您自己的设备上），确保为各种人工智能工具的用户提供更具包容性和响应性的体验。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评估被认为值得支持。影响审查标准。