CSR: Small: Cross-Layer Solutions Enabling Instant Computing for Edge Intelligence Devices

CSR：小：跨层解决方案为边缘智能设备提供即时计算

• 批准号: 2247156
• 负责人: Arman Roohi
• 金额: $ 53.39万
• 依托单位: University of Nebraska-Lincoln
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2247156&HistoricalAwards=false
• 关键词: CSR; Small; Cross; Layer; Solutions

Cloud-based computation and communication encounter several severe challenges, including high latency, questionable scalability, quality of service, privacy, and security. These issues can be addressed by transitioning computing architecture from a traditional cloud-centric mindset to a thing-centric (data-centric) perspective. However, nearly 90% of the data generated by the Internet of Things (IoT) is not analyzed using the conventional mechanism, due to limited computing ability and constraints in power and area. Hence, resource-limited IoTs should be developed optimally to enhance overall performance and extend lifetime. Our objective in this project is to transition from the conventional paradigm to a Sense-Decide-Action mechanism, which can analyze data locally, autonomously, and sustainably instead of sending it to the cloud, thereby reducing the amount of communication via a new cross-layer co-design approach. The broader impact and significance of our project lie in systematically paving the way for innovative foundational computing schemes. These strategies enable efficient instant computing and the necessary design approaches for real-time processing and decision-making systems. This progress brings us closer to the reality of accommodating over a trillion interconnected devices and improving the data privacy of resource-limited IoTs for critical applications, including healthcare monitoring, automotive applications, and industrial sensing. The technical approach of this research revolves around the development of low-overhead strategies to accelerate edge intelligence sensory nodes' autonomous operation within an environment. This is achieved by (1) designing and analyzing non-von-Neumann architectures, co-integrating conversion and processing capabilities in conjunction with an unconventional number system to alleviate the existing data movement issue between off/on-chip and processor; and (2) implementing processing units for both generic computations and domain-specific and emerging applications. This automated process of architecture engineering creates search space, defines design strategy, and identifies the optimal architecture to improve metrics such as lifetime energy reduction and overall performance. We evaluate the functionalities and performance of the proposed Thrusts through extensive modeling and simulations, beginning from circuit-level design and progressing upwards. This research effectively establishes novel lightweight heterogeneous edge intelligence capable of autonomously processing various data and compute-intensive tasks in an energy-scarce environment, marking a significant step towards the efficient future of IoT applications.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.

基于云的计算和通信遇到了一些严峻的挑战，包括高延迟、可扩展性、服务质量、隐私和安全性。这些问题可以通过将计算架构从传统的以云为中心的思维方式转变为以事物为中心（以数据为中心）的视角来解决。然而，由于计算能力有限以及功耗和面积的限制，物联网（IoT）产生的近90%的数据没有使用传统机制进行分析。因此，资源有限的物联网应该得到优化开发，以提高整体性能并延长使用寿命。我们在这个项目中的目标是从传统范式过渡到“感知-决定-行动”机制，该机制可以本地、自主、可持续地分析数据，而不是将其发送到云端，从而通过新的交叉方式减少通信量。层协同设计方法。我们项目更广泛的影响和意义在于系统地为创新的基础计算方案铺平道路。这些策略可以实现高效的即时计算以及实时处理和决策系统的必要设计方法。这一进展使我们更接近实现容纳超过一万亿个互连设备并改善关键应用（包括医疗保健监控、汽车应用和工业传感）资源有限的物联网的数据隐私的现实。 这项研究的技术方法围绕开发低开销策略来加速边缘智能传感节点在环境中的自主运行。这是通过以下方式实现的：（1）设计和分析非冯诺依曼架构，将转换和处理能力与非常规数字系统相结合，以缓解现有的片外/片上和处理器之间的数据移动问题； (2) 实现通用计算以及特定领域和新兴应用的处理单元。这种架构工程的自动化过程创建搜索空间，定义设计策略，并确定最佳架构以改进诸如寿命能耗降低和整体性能等指标。我们通过广泛的建模和仿真来评估所提出的 Thrusts 的功能和性能，从电路级设计开始一直向上。这项研究有效地建立了新颖的轻量级异构边缘智能，能够在能源稀缺的环境中自主处理各种数据和计算密集型任务，标志着物联网应用的高效未来迈出了重要一步。该奖项反映了 NSF 的法定使命，并被认为是值得的通过使用基金会的智力优势和更广泛的影响审查标准进行评估来获得支持。