TEMPO: Time Driven Modelling and Resource Management of Real-Time Systems on Multiprocessor Systems-on-Chip

在多处理器片上系统（MPSoC）平台上实现的嵌入式实时系统（Erts）对系统行为的离线建模、运行时系统时间和资源使用的离线预测以及运行时资源管理提出了根本性的挑战。MPSoC平台通过并行性提供了巨大计算能力的前景，但是这种并行性使得它们难以建模。因此，从实时系统的角度来看，这是非常困难的离线预测MPSoC平台上实现的Erts的运行时行为和性能。我们注意到，这种预测是实时系统的基本要求。从时间和资源使用的角度理解和预测系统性能要求应用和系统软件、资源管理和MPSoC平台的足够方面必须被准确地建模，以建立应用软件、系统软件和MPSoC平台之间的复杂的相互依赖性。如果没有这种理解，就很难离线验证系统是否满足其时序要求和资源使用限制（例如，内存）。观察到这样的系统本质上是动态的，这加剧了研究的挑战：应用程序配置（或模式）的变化，应用程序软件在处理元素之间的移动，可用资源的变化（例如，功率）、硬件平台本身的配置的变化（即，该项目通过倡导一种将时间（而不是结构或功能行为）置于建模方法、运行时资源管理和离线验证方法的中心的方法，直接解决了理解在MPSoC平台上实现的动态Erts的行为的挑战。采用以时间为中心的复杂并行系统的观点背后的直觉是观察到传统的功能或结构方法不可避免地隐藏或混淆相关的非功能系统的时序行为。我们相信，通过从时间的角度对系统进行建模，我们可以在不同的时间粒度（从应用程序到硬件）对所有行为进行建模和关联，从而实现对时间属性的准确离线分析和预测-这对实时系统至关重要。该项目将专注于三个具体的挑战领域：建模，资源管理和验证。我们将开发一个面向资源的时间段框架，使系统进行建模。这将支持资源管理政策和机制并与之相结合。后者将基于分层合同，采用资源虚拟化方法，扩展到包括多处理器，内存层次结构，片上网络，能源和空间。验证将通过为资源合同开发适当的调度和分配算法来实现，包括严格的分析（即，可扩展性分析）和模拟。重要的是，该项目将在每个时间粒度级别上利用建模、资源管理和验证的集成方法。

Embedded real-time systems (ERTS) implemented on Multiprocessor System-on-Chip (MPSoC) platforms present fundamental challenges to the offline modeling of system behaviour, offline prediction of system temporal and resource usage at run-time, and run-time resource management. MPSoC platforms offer the prospect of immense computational power via parallelism, but this very parallelism makes them difficult to model. Hence from a real-time systems perspective, it is extremely difficult to predict offline the run-time behaviour and performance of ERTS implemented upon MPSoC platforms. We note that such predictions are a fundamental requirement of real-time systems. Understanding and predicting system performance from a time and resource usage perspective requires that sufficient aspects of the application and system software, resource management and MPSoC platform must be accurately modeled to establish the complex inter-dependencies between application software, system software and the MPSoC platform. Without this understanding, it is difficult to verify offline that a system will meet its timing requirements and resource usage constraints (eg. memory). The research challenge is exacerbated by observing that such systems are essentially dynamic: application configuration (or mode) changes, movement of application software between processing elements, changes in available resource (eg. power), changes in the configuration of the hardware platform itself (ie. functionally dynamically reconfigurable).This project directly addresses the challenge of understanding the behaviour of dynamic ERTS implemented on MPSoC platforms by advocating an approach that puts time (rather than structure or functional behaviour) at the centre of the modeling method, run-time resource management and offline verification approach. The intuition behind adopting a time-centric view of complex parallel systems is the observation that conventional functional or structural approaches inevitably hide or obfuscate pertinent non-functional system timing behaviour. We believe that by modeling the system from the perspective of time, we can model and relate all behaviours at differing time granularities (from application to hardware), so enabling accurate offline analysis and prediction of timing properties - essential for real-time systems.The project will focus upon three specific areas of the challenge: modeling, resource management and verification. We will develop a resource oriented time banded framework to allow the system to be modeled. This will support and integrate with resource management policies and mechanisms. The latter will be based upon hierarchical contracts, taking a resource virtualisation approach expanded to include multiprocessors, memory hierarchies, on-chip networks, energy and space. Verification will be achieved by developing appropriate scheduling and allocation algorithms for the resource contracts, incorporating both rigorous analysis (ie. schedulability analysis) and simulation. Importantly, the project will utilise an integrated approach across modeling, resource management and verification at each level of timing granularity.