In a hard real-time embedded system, the time at which a result is computed is as important as the result itself. Modern processors go to extreme lengths to ensure their function is predictable, but have abandoned predictable timing in favor of average-case performance. Real-time operating systems provide timing-aware scheduling policies, but without precise worst-case execution time bounds they cannot provide guarantees.We describe an alternative in this paper: a SPARC-based processor with predictable timing and instruction-set extensions that provide precise timing control. Its pipeline executes multiple, independent hardware threads to avoid costly, unpredictable bypassing, and its exposed memory hierarchy provides predictable latency. We demonstrate the effectiveness of this precision-timed (PRET) architecture through example applications running in simulation.
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In a component-based design context, we propose a relational interface theory for synchronous systems. A component is abstracted by its interface, which consists of input and output variables, as well as one or more contracts. A contract is a relation between input and output assignments. In the stateless case, there is a single contract that holds at every synchronous round. In the general, stateful, case, the contract may depend on the state, modeled as the history of past observations. Interfaces can be composed by connection or feedback. Parallel composition is a special case of connection. Feedback is allowed only for Moore interfaces, where the contract does not depend on the current values of the input variables that are connected (although it may depend on past values of such variables). The theory includes explicit notions of environments, pluggability and substitutability. Environments are themselves interfaces. Pluggability means that the closed-loop system formed by an interface and an environment is well-formed, that is, a state with unsatisfiable contract is unreachable. Substitutability means that an interface can replace another interface in any environment. A refinement relation between interfaces is proposed, that has two main properties: first, it is preserved by composition; second, it is equivalent to substitutability for well-formed interfaces. Shared refinement and abstraction operators, corresponding to greatest lower and least upper bounds with respect to refinement, are also defined. Input-complete interfaces, that impose no restrictions on inputs, and deterministic interfaces, that produce a unique output for any legal input, are discussed as special cases, and an interesting duality between the two classes is exposed. A number of illustrative examples are provided, as well as algorithms to compute compositions, check refinement, and so on, for finite-state interfaces.
Abstract. Including semantic information in models helps to expose modeling errors early in the design process, engage a designer in a deeper understanding of the model, and standardize concepts and terminology across a development team. It is impractical, however, for model builders to manually annotate every modeling element with semantic properties. This paper demonstrates a correct, scalable and automated method to infer semantic properties using lattice-based ontologies, given relatively few manual annotations. Semantic concepts and their relationships are formalized as a lattice, and relationships within and between components are expressed as a set of constraints and acceptance criteria relative to the lattice. Our inference engine automatically infers properties wherever they are not explicitly specified. Our implementation leverages the infrastructure in the Ptolemy II type system to get efficient and scalable inference and consistency checking. We demonstrate the approach on a non-trivial Ptolemy II model of an adaptive cruise control system.
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