The shift towards parallel computing witnessed since the turn of this century has forced us to rethink traditional software design paradigms to better utilize resources. Yet, the simulation of time-aware systems remains a challenging topic due to the inherent semantics of time and causality whose consistency needs to be controlled, traditionally in form of a global event queue, limiting the potential for parallel exploitation. We propose a rehash of this problem by tackling it from a different modeling perspective, one which is able to express concurrency more naturally, i.e. dataflow (DF) models of computation (MoCs). By abstracting time aspects as an algebra hosted on a pure DF MoC, we are able to apply recent results from MoC theory not only for the purpose of describing deterministic behaviors for distributed timed systems, but also to overcome the existing limitations of timed execution in order to increase a simulation model's performance. We use a well-known example of a deadlock-prone distributed discrete event system as a driver to introduce the modeling concepts and show their potential for parallelism.
This book is a living document which gathers material related to ForSyDe-Atom and binds it in form of a user manual. Most of the text contained by this book originates from actual inline or literate source code documentation, in form of examples, tutorials, reports and even library API documentation. This means that this document evolves with the ForSyDe-Atom project itself and is periodically updated.
The annotated slides can be considered complementary to the paper, and are recommended for a gentler introduction to an otherwise dense material. The case study is different than in the paper and it is meant to guide step-by-step into understanding the new concepts.
When designing complex mixed-critical systems on multiprocessor platforms, a huge number of design alternatives has to be evaluated. Therefore, there is a need for tools which systematically find and analyze the ample alternatives and identify solutions that satisfy the design constraints. The recently proposed design space exploration (DSE) tool DeSyDe uses constraint programming (CP) to find implementations with performance guarantees for multiple applications with potentially mixed-critical design constraints on a shared platform. A key component of the DeSyDe tool is its throughput analysis component, called a throughput propagator in the context of CP. The throughput propagator guides the exploration by evaluating each design decision and is therefore executed excessively throughout the exploration. This paper presents two throughput propagators based on different analysis methods for DeSyDe. Their performance is evaluated in a range of experiments with six different application graphs, heterogeneous platform models and mixed-critical design constraints. The results suggest that the MCR throughput propagator is more efficient.
Designing cyber-physical systems is highly challenging due to its manifold interdependent aspects such as composition, timing, synchronization and behavior. Several formal models exist for description and analysis of these aspects, but they focus mainly on a single or only a few system properties. We propose a formal composable framework which tackles these concerns in isolation, while capturing interaction between them as a single layered model. This yields a holistic, fine-grained, hierarchical and structured view of a cyber-physical system. We demonstrate the various benefits for modeling, analysis and synthesis through a typical example.