This paper addresses the design of reactive real-time embedded systems. Such systems are often heterogeneous in implementation technologies and design styles, for example by combining hardware ASICs with embedded software. The concurrent design process for such embedded systems involves solving the specification, validation, and synthesis problems. We review the variety of approaches to these problems that have been taken.

In this paper we present an approach for quantitative analysis of application-specific dataflow architectures. The approach allows the designer to rate design alternatives in a quantitative way and therefore supports him in the design process to find better performing architectures. The context of our work is Video Signal Processing algorithms which are mapped onto weakly-programmable, coarse-grain dataflow architectures. The algorithms are represented as Kahn graphs with the functionality of the nodes being coarse-grain functions. We have implemented an architecture simulation environment that permits the definition of dataflow architectures as a composition of architecture elements, such as functional units, buffer elements and communication structures. The abstract, clockcycle accurate simulator has been built using a multi-threading package and employs object oriented principles. This results in a configurable and efficient simulator. Algorithms can subsequently be executed on the architecture model producing quantitative information for selected performance metrics. Results are presented for the simulation of a realistic application on several dataflow architecture alternatives, showing that many different architectures can be simulated in modest time on a modern workstation.

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The science of computation has systematically abstracted away the physical world. Embedded software systems, however, engage the physical world. Time, concurrency, liveness, robustness, continuums, reactivity, and resource management must be remarried to computation. Prevailing abstractions of computational systems leave out these "non-functional" aspects. This chapter explains why embedded software is not just software on small computers, and why it therefore needs fundamentally new views of computation. It suggests component architectures based on a principle called "actor-oriented design," where actors interact according to a model of computation, and describes some models of computation that are suitable for embedded software. It then suggests that actors can define interfaces that declare dynamic aspects that are essential to embedded software, such as temporal properties. These interfaces can be structured in a "system-level type system" that supports the sort of design-time and run-time type checking that conventional software benefits from.

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Typical embedded hardware/software systems are implemented using a combination of C and an HDL such as Verilog. While each is well-behaved in isolation, combining the two gives a nondeterministic model whose ultimate behavior must be validated through expensive (cycle-accurate) simulation. We propose an alternative for describing such systems. Our SHIM (software/hardware integration medium) model, effectively Kahn networks with rendezvous communication, provides deterministic concurrency. We present the Tiny-SHIM language for such systems and its semantics, demonstrate how to implement it in hardware and software, and discuss how it can be used to model a real-world system. By providing a powerful, deterministic formalism for expressing systems, designing systems and verifying their correctness will become easier.

Kahn process networks (KPNs) are a programming paradigm suitable for streaming-based multimedia and signal-processing applications.

Dataflow models of computation have intrigued computer scientists since the 1970s. They were first introduced by Jack Dennis as a basis for parallel programming languages and architectures, and by Gilles Kahn as a model of concurrency. Interest in these models of computation has been recently rekindled by the resurrection of parallel computing, due to the emergence of multicore architectures. However, Dennis and Kahn approached dataflow very differently. Dennis ’ approach was based on an operational notion of atomic firings driven by certain firing rules. Kahn’s approach was based on a denotational notion of processes as continuous functions on infinite streams. This paper bridges the gap between these two points of view, showing that sequences of firings define a continuous Kahn process as the least fixed point of an appropriately constructed functional. The Dennis firing rules are sets of finite prefixes satisfying certain conditions that ensure determinacy. These conditions result in firing rules that are strictly more general than the blocking reads of the Kahn-MacQueen implementation of Kahn process networks, and solve some compositionality problems in the dataflow model. 1

In this paper, an approach to symbolic model checking of process networks is introduced. It is based on interval decision diagrams (IDDs), a representation of multi-valued functions. Compared to other model checking strategies, IDDs show some important properties that enable the verification of process networks more adequately than with conventional approaches. Additionally, applications concerning scheduling will be shown. A new form of transition relation representation called interval mapping diagrams (IMDs)---and their less general version predicate action diagrams (PADs)---is explained together with the corresponding methods. 1 Introduction Process network models---consisting in general of concurrent processes communicating through unidirectional FIFO queues---as that of Kahn [7, 8] are commonly used, e.g., for specification and synthesis of distributed systems. They form the basis for applications such as real-time scheduling and allocation. Many other models of computation, ...

Modeling applications and architectures at various levels of abstraction is becoming more and more an accepted approach in embedded system design. When looking at the modeling of applications in the domain of video, audio, and graphics applications, we notice that they exhibit a high degree of task parallelism and operate on streams of data. Models that we can use to specify such stream-based applications on a high level of abstraction are the dataflow models and process network models. Each of these models has its own merits. Therefore, an alternative approach is to introduce a model of computation that combines the semantics of both models of computation. In this paper, we introduce such a model of computation, which we call the Stream-Based Functions (SBF) model of computation and show an example. Furthermore, we discuss the composition and decomposition of SBF objects and put the SBF model of computation in the context of relevant dataflow models and process network models.