Exploiting Hardware/Software Interactions for Analyzing Embedded Systems

Abstract

Embedded systems are often subject to real-time timing constraints. Such systems require determinism to ensure that task deadlines are met. The knowledge of the bounds on worst-case execution times (WCET) of tasks is a critical piece of information required to achieve this objective. One limiting factor in designing real-time systems is the class of processors that may be used. Contemporary processors with their advanced architectural features, such as out-of-order execution, branch prediction, speculation, and prefetching, cannot be statically analyzed to obtain WCETs for tasks as they introduce non-determinism into task execution, which can only be resolved at run-time. Such micro-processors are tuned to reduce average-case execution times at the expense of predictability. Hence, they do not find use in hard real-time systems. On the other hand, static timing analysis derives bounds on WCETs but requires that bounds on loop iterations be known statically, i.e., at compile time. This limits the class of applications that may be analyzed by static timing analysis and, hence, used in a real-time system. Finally, many embedded systems have communication and⁄or synchronization constructs and need to function on a wide spectrum of hardware devices ranging from small microcontrollers to modern multi-core architectures. Hence, any single analysis technique (be it static or dynamic) will not suffice in gauging the true nature of such systems.

This thesis contributes novel techniques that use combinations of analysis methods and constant interactions between them to tackle complexities in modern embedded systems. To be more specific, this thesis (I) introduces of a new paradigm that proposes minor enhancements to modern processor architectures, which, on interaction with software modules, is able to obtain tight, accurate timing analysis results for modern processors; (II) it shows how the constraint concerning statically bound loops may be relaxed and applied to make dynamic decisions at run-time to achieve power savings; (III) it represents the temporal behavior of distributed real-time applications as colored graphs coupled with graph reductions/transformations that attempt to capture inherent "meaning" in the application. To the best of my knowledge, these methods that utilize interactions between different sources of information to analyze modern embedded systems are a first of their kind.