CSR: Small: The Deterministic Memory Approach for Predictable and High Performance Cyber Physical Systems

高性能嵌入式多核平台对于网络物理系统（CPS）变得越来越重要，尤其是在汽车和航空领域，可以通过整合降低成本、尺寸、重量和能耗。然而，多核平台的时间可预测性差是安全关键型CPS的主要障碍。这个项目将通过提出一个新的内存抽象来解决时间可预测性问题，称为确定性内存，它可以实现软件和硬件之间的有效跨层协作。利用抽象和架构扩展，资源管理技术和分析方法将被开发，以实现可预测的和高效的多核系统中的实时计算。该项目将展示拟议的确定性内存抽象如何实现软件和硬件设计的创新。该项目将开发新的时序分析方法，将纳入新的内存概念，这有可能显着减少多核实时系统的理论和实践之间的差距。该项目将通过提高系统的可预测性和确定性而不过度配置资源来推进安全关键CPS领域，如汽车和航空。该研究有望实现具有不同关键性的多个任务的有效整合，从而降低成本并降低系统的尺寸，重量和功耗要求。此外，该研究有可能通过提供更强的硬件支持来帮助降低航空业的认证成本。考虑到汽车行业的市场规模和航空业的高认证成本，研究承诺的预期改进可能会节省数十亿美元。

High-performance embedded multicore platforms are becoming increasingly important for cyber-physical systems (CPS) - especially in automotive and aviation domains - to reduce cost, size, weight, and energy consumption through consolidation. However, poor time predictability of multicore platforms is a major hurdle for safety-critical CPS. This project will address the time predictability problem by proposing a new memory abstraction, called Deterministic Memory, that enables effective cross-layer collaborations between software and hardware. Leveraging abstraction and architecture extensions, resource management techniques and analysis methodologies will be developed to realize predictable and efficient real-time computing in multicore systems.The project will demonstrate how the proposed Deterministic Memory abstraction enables innovations in software and hardware designs. The project will develop new timing analysis methodologies that will incorporate the new memory concepts, which have the potential to significantly reduce the gap between theory and practice in multicore real-time systems. The project will advance safety-critical CPS domains, such as automotive and aviation, by improving predictability and determinism of the systems without over-provisioning of resources.The research is expected to enable efficient consolidation of multiple tasks with different criticality, and thereby to cut the cost and reduce the size, weight, and power requirements of the system. Moreover, the research has the potential to help reduce certification cost of aviation industry by providing stronger isolation with hardware support. Considering the market size of automotive industry and the high certification cost in aviation industry, the expected improvements promised by the research represent potentially billions of dollars in savings.