One of the main challenges of embedded system design lies in the natural heterogeneity of these systems. We can say that embedded systems are electronic systems designed and programmed to tackle a specific application...
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One of the main challenges of embedded system design lies in the natural heterogeneity of these systems. We can say that embedded systems are electronic systems designed and programmed to tackle a specific application. Each application has its requirements, although embedded systems often combine many domain-specific subsystems. Considering this context, the design of embedded systems can be extremely challenging, including system modeling, simulation, formal verification, and the synthesis to a correct implementation. To manage the complexity of such systems, the design should start at higher levels of abstraction, based on formal models, without considering the low-level characteristics of the underlying software or hardware. These high-level formal meta-models, named models of computation (MoC), define a set of rules that dictate how computation should be performed and how they should communicate with each other, along with other information such as the notion of time. In this paper, we present as the main contribution a set of rules and interfaces that enable the proper mixing of different MoC domains in a framework for complex embedded system design, thus allowing a heterogeneous system composition at a high abstraction level, including the synchronous reactive, synchronous dataflow, and scenario-aware dataflow MoCs. We model both part of an avionic system and a reconfigurable RISC-V processor using these MoCs and the proposed interfaces as a case study showing the applicability brought by our proposal.
Dynamical systems and physical models defined on idealized continuous phase spaces are known to exhibit non-computable phenomena;examples include the wave equation, recurrent neural networks, or Julia sets in holomorp...
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Dynamical systems and physical models defined on idealized continuous phase spaces are known to exhibit non-computable phenomena;examples include the wave equation, recurrent neural networks, or Julia sets in holomorphic dynamics. Inspired by the works of Moore and Siegelmann, we show that ideal fluids, modeled by the Euler equations, are capable of simulating poly-time Turing machines with polynomial advice on compact three-dimensional domains. This is precisely the complexity class P =poly considered by Siegelmann in her study of analog recurrent neural networks. In addition, we introduce a new class of symbolic systems, related to countably piecewise linear transformations of the unit square, that is capable of simulating Turing machines with advice in real-time, contrary to previously known models.
A model of computation provides a set of governing principles and a discipline determining the objects, their interrelationships, parallel flow control, and distribution. In so doing it provides a conceptual framework...
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A model of computation provides a set of governing principles and a discipline determining the objects, their interrelationships, parallel flow control, and distribution. In so doing it provides a conceptual framework for the co-design and operation for all layers of the software and hardware architecture system stack from programming model through system software to processor core instruction set and structures. As enabling technologies advance changing capabilities, balance, and design challenges, the response has been a phase change in how HPC systems are realized reflected by the development and adoption of new models of computation to best fit the emerging underlying technology conditions. This has occurred at least through five technology epochs in the past and the field is entering a sixth such with the heterogeneous multicore Petaflops decade. A brief presentation of the nature and characteristics of models of computation is offered here to contribute to the current community discussions on how to proceed towards the realization of the promise of practical Exascale computing by the end of the next decade.
The increased interactivity and connectivity of computational devices along with the spreading of computational tools and computational thinking across the fields, has changed our understanding of the nature of comput...
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The increased interactivity and connectivity of computational devices along with the spreading of computational tools and computational thinking across the fields, has changed our understanding of the nature of computing. In the course of this development computing models have been extended from the initial abstract symbol manipulating mechanisms of stand-alone, discrete sequential machines, to the models of natural computing in the physical world, generally concurrent asynchronous processes capable of modelling living systems, their informational structures and dynamics on both symbolic and sub-symbolic information processing levels. Present account of models of computation highlights several topics of importance for the development of new understanding of computing and its role: natural computation and the relationship between the model and physical implementation, interactivity as fundamental for computational modelling of concurrent information processing systems such as living organisms and their networks, and the new developments in logic needed to support this generalized framework. Computing understood as information processing is closely related to natural sciences;it helps us recognize connections between sciences, and provides a unified approach for modeling and simulating of both living and non-living systems.
Cyber-physical systems (CPS) and embedded systems have a large application domain, from simple consumer electronics products to complex systems with restricted safety requirements, such as avionics systems. As broadly...
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ISBN:
(纸本)9798350333572
Cyber-physical systems (CPS) and embedded systems have a large application domain, from simple consumer electronics products to complex systems with restricted safety requirements, such as avionics systems. As broadly known in the case of avionics systems, the occurrence of a failure can cause disastrous consequences. In this sense, the design of complex CPS can be made by using a formal approach, based on models of computation. Model of computation (MoC) is a set of rules that describe the semantics of both execution and concurrency in heterogeneous computational systems. MoCs can be categorized as timed or untimed. As an example, the synchronous (SY) model of computation is a timed MoC, whereas the synchronous dataflow (SDF) and the scenario-aware dataflow (SADF) are untimed. Yet, there are some gaps to fill in this context. For example, which is the MoC which better describes the application-specific requirements at a high level of abstraction while also being able to reach a feasible platform model implementation with required performance, and most importantly, without losing the characteristics and properties of the application domain. In this paper, we perform an analysis of the most commons models of computation (e.g., SY, SDF, and SADF) and demonstrate which one better fits the avionics systems domain, while at the same time being capable to provide a safe implementation of future digital avionics systems.
Today, developments of Real Time Embedded Systems have to face new challenges. On the one hand, Tune-To-Market constraints require a reliable development process allowing quick design space exploration. On the other h...
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ISBN:
(纸本)9783642135941
Today, developments of Real Time Embedded Systems have to face new challenges. On the one hand, Tune-To-Market constraints require a reliable development process allowing quick design space exploration. On the other hand, rapidly developing technology, as stated by Moore's law, requires techniques to handle the resulting productivity gap. In a previous paper, we have presented our Model Based Engineering methodology addressing those issues. In this paper, we make a focus on models of computation design and analysis. We illustrate our approach on a Cognitive Radio System development implemented on an FPGA. Tins work is part of the MoPCoM research project gathering academic and industrial organizations (http://***).
The goal of the presented paper is to provide an introduction to the basic computational models used in quantum information theory. We review various models of quantum Turing machine, quantum circuits and quantum rand...
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The goal of the presented paper is to provide an introduction to the basic computational models used in quantum information theory. We review various models of quantum Turing machine, quantum circuits and quantum random access machine (QRAM) along with their classical counterparts. We also provide an introduction to quantum programming languages, which are developed using the QRAM model. We review the syntax of several existing quantum programming languages and discuss their features and limitations.
Power consumption has become one of the most critical concerns for processor design. This motivates designing algorithms for minimum execution time subject to energy constraints. We propose simple models for analysing...
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ISBN:
(纸本)9780769534718
Power consumption has become one of the most critical concerns for processor design. This motivates designing algorithms for minimum execution time subject to energy constraints. We propose simple models for analysing algorithms that reflect the energy-time trade-offs of CMOS circuits. Using these models, we derive lower bounds for the energy-constrained execution time of sorting, addition and multiplication, and we present algorithms that meet these bounds. We show that minimizing time under energy constraints is not the same as minimizing operation count or computation depth.
This Special Issue of Information and computation contains selected papers from two editions (2021 and 2022) of EXPRESS/SOS, the Combined International Workshop on Expressiveness in Concurrency (EXPRESS) and Structura...
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This paper presents two weak partially synchronous system models Manti(n-k) and Msink(n-k), which are just strong enough for solving k-set agreement: We introduce the generalized (n-k)-loneliness failure detector L(k)...
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This paper presents two weak partially synchronous system models Manti(n-k) and Msink(n-k), which are just strong enough for solving k-set agreement: We introduce the generalized (n-k)-loneliness failure detector L(k), which we first prove to be sufficient for solving k-set agreement, and show that L(k) but not L(k-1) can be implemented in both models. Manti(n-k) and Msink(n-k) are hence the first message passing models that lie between models where V (and therefore consensus) can be implemented and the purely asynchronous model. We also address k-set agreement in anonymous systems, that is, in systems where (unique) process identifiers are not available. Since our novel k-set agreement algorithm using L(k) also works in anonymous systems, it turns out that the loneliness failure detector L = L(n-1) introduced by Delporte et al. is also the weakest failure detector for set agreement in anonymous systems. Finally, we analyze the relationship between L(k) and other failure detectors suitable for solving k-set agreement.
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