74 research outputs found

    Polychronous Interpretation of Synoptic, a Domain Specific Modeling Language for Embedded Flight-Software

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    The SPaCIFY project, which aims at bringing advances in MDE to the satellite flight software industry, advocates a top-down approach built on a domain-specific modeling language named Synoptic. In line with previous approaches to real-time modeling such as Statecharts and Simulink, Synoptic features hierarchical decomposition of application and control modules in synchronous block diagrams and state machines. Its semantics is described in the polychronous model of computation, which is that of the synchronous language Signal.Comment: Workshop on Formal Methods for Aerospace (FMA 2009

    Polychronous mode automata

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    International audienceAmong related synchronous programming principles, the model of computation of the Polychrony workbench stands out by its capability to give high-level description of systems where each component owns a local activation clock (such as, typically,distributed real-time systems or systems on a chip). In order to bring the modeling capability of Polychrony to the context of a model-driven engineering toolset for embedded system design, we define a diagramic notation composed of mode automata and data-flow equations on top of the multi-clocked synchronous model of computation supported by the Polychrony workbench. We demonstrate the agility of this paradigm by considering the example of an integrated modular avionics application. Our presentation features the formalization and use of model transformation techniques of the GME environment to embed the extension of Polychrony's meta-model with mode automata

    A Survey of Desynchronization in a Polychronous Model of Computation

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    AbstractThe synchronous hypothesis arose in the late Eighties as a conceptual framework for the computer-aided design of embedded systems. Along with this framework, the issue of desynchronization was simultaneously raised as the major topic of mapping the ideal communication and computation model of synchrony on realistic and distributed computer architectures.The aim of the present article is to survey the development of this topics in the particular yet promising model of one of the prominent environments that were build along these principles: Signal and its polychronous (synchronous multi-clocked) model of computation, before to give some hints and ideas about ongoing research addressing this issue

    TESL: A Model with Metric Time for Modeling and Simulation

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    Real-time and distributed systems are increasingly finding their way into critical embedded systems. On one side, computations need to be achieved within specific time constraints. On the other side, computations may be spread among various units which are not necessarily sharing a global clock. Our study is focused on a specification language - named TESL - used for coordinating concurrent models with timed constraints. We explore various questions related to time when modeling systems, and aim at showing that TESL can be introduced as a reasonable balance of expressiveness and decidability to tackle issues in complex systems. This paper introduces (1) an overview of the TESL language and its main properties (polychrony, stutter-invariance, coinduction for simulation), (2) extensions to the language and their applications

    Adaptivity in High-Performance Embedded Systems: a Reactive Control Model for Reliable and Flexible Design

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    International audienceSystem adaptivity is increasingly demanded in high-performance embedded systems, particularly in multimedia System-on-Chip (SoC), due to growing Quality of Service requirements. This paper presents a reactive control model that has been introduced in Gaspard, our framework dedicated to SoC hardware/software co-design. This model aims at expressing adaptivity as well as reconïŹgurability in systems performing data-intensive computations. It is generic enough to be used for description in the different parts of an embedded system, e.g. speciïŹcation of how different data-intensive algorithms can be chosen according to some computation modes at the functional level; expression of how hardware components can be selected via the usage of a library of Intellectual Properties (IPs) according to execution performances. The transformation of this model towards synchronous languages is also presented, in order to allow an automatic code generation usable for formal veriïŹcation, based of techniques such as model checking and controller synthesis as illustrated in the paper. This work, based on Model-Driven Engineering and the standard UML MARTE proïŹle, has been implemented in Gaspard

    Formal semantics of behavior specifications in the architecture analysis and design language standard

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    In system design, an architecture speciïŹcation or model serves, among other purposes, as a repository to share knowledge about the system being designed. Such a repository enables automatic generation of analytical models for diïŹ€erent aspects relevant to system design (timing, reliability, security, etc.). The Architecture Analysis and Design Language (AADL) is a standard proposed by SAE to express architecture speciïŹcations and share knowledge between the diïŹ€erent stakeholders about the system being designed. To support unambiguous reasoning, formal veriïŹcation, high-ïŹdelity simulation of architecture speciïŹcations in a model-based AADL design workïŹ‚ow, we have deïŹned a formal semantics for the behavior speciïŹcation of the AADL, the presentation of this semantics is the aim of this paper

    Design for a Darwinian Brain: Part 1. Philosophy and Neuroscience

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    Physical symbol systems are needed for open-ended cognition. A good way to understand physical symbol systems is by comparison of thought to chemistry. Both have systematicity, productivity and compositionality. The state of the art in cognitive architectures for open-ended cognition is critically assessed. I conclude that a cognitive architecture that evolves symbol structures in the brain is a promising candidate to explain open-ended cognition. Part 2 of the paper presents such a cognitive architecture.Comment: Darwinian Neurodynamics. Submitted as a two part paper to Living Machines 2013 Natural History Museum, Londo

    Spatio-temporal pattern recognizers using spiking neurons and spike-timing-dependent plasticity.

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    It has previously been shown that by using spike-timing-dependent plasticity (STDP), neurons can adapt to the beginning of a repeating spatio-temporal firing pattern in their input. In the present work, we demonstrate that this mechanism can be extended to train recognizers for longer spatio-temporal input signals. Using a number of neurons that are mutually connected by plastic synapses and subject to a global winner-takes-all mechanism, chains of neurons can form where each neuron is selective to a different segment of a repeating input pattern, and the neurons are feed-forwardly connected in such a way that both the correct input segment and the firing of the previous neurons are required in order to activate the next neuron in the chain. This is akin to a simple class of finite state automata. We show that nearest-neighbor STDP (where only the pre-synaptic spike most recent to a post-synaptic one is considered) leads to "nearest-neighbor" chains where connections only form between subsequent states in a chain (similar to classic "synfire chains"). In contrast, "all-to-all spike-timing-dependent plasticity" (where all pre- and post-synaptic spike pairs matter) leads to multiple connections that can span several temporal stages in the chain; these connections respect the temporal order of the neurons. It is also demonstrated that previously learnt individual chains can be "stitched together" by repeatedly presenting them in a fixed order. This way longer sequence recognizers can be formed, and potentially also nested structures. Robustness of recognition with respect to speed variations in the input patterns is shown to depend on rise-times of post-synaptic potentials and the membrane noise. It is argued that the memory capacity of the model is high, but could theoretically be increased using sparse codes
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