Computer Architecture

计算机架构

• 批准号: CRC-2018-00104
• 负责人: EnrightJerger, Natalie
• 金额: $ 8.74万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Canada Research Chairs
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=730374
• 关键词: Computer; Architecture

Processing is no longer limited to desktops and datacenters, and more diverse and unconventional processors are required to keep pace with the growing need for better computational capacity. The Internet-of-Things (IoT) brings us a richly connected set of ultra-low power processors that can sense and collect data remotely from their environment, but the data collected must be computed securely and privately. Machine learning is a promising approach to gathering insight from such large volumes of data. This research will deliver groundbreaking advances in processor innovations that improve performance, energy efficiency, and security for battery-less IoT devices and machine learning applications.

处理不再局限于桌面和数据中心，需要更加多样化和非传统的处理器来满足对更好计算能力不断增长的需求。物联网 (IoT) 为我们带来了一组连接丰富的超低功耗处理器，这些处理器可以从环境中远程感知和收集数据，但收集的数据必须安全且私密地进行计算。机器学习是从如此大量的数据中收集洞察力的一种很有前途的方法。这项研究将在处理器创新方面取得突破性进展，从而提高无电池物联网设备和机器学习应用的性能、能源效率和安全性。