Framework For Efficient Cosimulation And Fast Prototyping on Multi-Components With AAA Methodology: LAR Codec Study Case

pp 1667 - 1671Real-time signal and image applications have significant time constraints involving the use of several powerful calculation units. Programmable multi-component architectures have proven to be a suitable solution combining flexibility and computation power. This paper presents a methodology for the fast design of signal and image processing applications. In a unified framework, application modeling, cosimulation and fast implementation onto parallel heterogeneous architectures are enabled and help to reduce time-to-market. Moreover, automatic code generation provides a high abstraction level for users. Finally, the worthwhile nature of Matlab/C language cosimulation is illustrated on a still image codec named LAR

Business models for distributed-simulation orchestration and risk management

Nowadays, industries are implementing heterogeneous systems from different domains, backgrounds, and operating systems. Manufacturing systems are becoming more and more complex, which forces engineers to manage the complexity in several aspects. Technical complexities bring interoperability, risk management, and hazards issues that must be taken into consideration, from the business model design to the technical implementation. To solve the complexities and the incompatibilities between heterogeneous components, several distributed and cosimulation standards and tools can be used for data exchange and interconnection. High-level architecture (HLA) and functional mockup interface (FMI) are the main international standards used for distributed and cosimulation. HLA is mainly used in academic and defense domains while FMI is mostly used in industry. In this article, we propose an HLA/FMI implementation with a connection to an external business process-modeling tool called Papyrus. Papyrus is configured as a master federate that orchestrates the subsimulations based on the above standards. The developed framework is integrated with external heterogeneous components through an FMI interface. This framework is developed with the aim of bringing interoperability to a system used in a power generation compan

On mixed abstraction, languages and simulation approach to refinement with SystemC AMS

Executable specifications and simulations arecornerstone to system design flows. Complex mixed signalembedded systems can be specified with SystemC AMSwhich supports abstraction and extensible models of computation. The language contains semantics for moduleconnections and synchronization required in analog anddigital interaction. Through the synchronization layer, user defined models of computation, solvers and simulators can be unified in the SystemC AMS simulator for achieving low level abstraction and model refinement. These improvements assist in amplifying model aspects and their contribution to the overall system behavior. This work presents cosimulating refined models with timed data flow paradigm of SystemC AMS. The methodology uses Cbased interaction between simulators. An RTL model ofdata encryption standard is demonstrated as an example.The methodology is flexible and can be applied in earlydesign decision trade off, architecture experimentation and particularly for model refinement and critical behavior analysis

Modeling Power Consumption and Temperature in TLM Models

International audienceMany techniques and tools exist to estimate the power consumption and the temperature map of a chip. These tools help the hardware designers develop power efficient chips in the presence of temperature constraints. For this task, the application can be ignored or at least abstracted by some high level scenarios; at this stage, the actual embedded software is generally not available yet. However, after the hardware is defined, the embedded software can still have a significant influence on the power consumption; i.e., two implementations of the same application can consume more or less power. Moreover, the actual software powe

An approach to design smart grids and their IT system by cosimulation

International audienceSmart grids are the oncoming generation of power grids, which rely on information and communication technologies to tackle decentralized and intermittent energy sources such as wind farms and photovoltaic plants. They integrate electronics, software information processing and telecommunications technical domains. Therefore the design of smart grids is complex because of the various technical domains and modeling tools at stake. In this article, we present an approach to their design, which relies on model driven engineering, executable models and FMI based cosimulation. This approach is illustrated on the use case of an insular power grid and allows to study the impact of power production decision

Measuring Occupants' Behaviour for Buildings' Dynamic Cosimulation

Measuring and identifying human behaviours are key aspects to support the simulation processes that have a significant role in buildings' (and cities') design and management. In fact, layout assessments and control strategies are deeply influenced by the prediction of building performance. However, the missing inclusion of the human component within the building-related processes leads to large discrepancies between actual and simulated outcomes. This paper presents a methodology for measuring specific human behaviours in buildings and developing human-in-the-loop design applied to retrofit and renovation interventions. The framework concerns the detailed building monitoring and the development of stochastic and data-driven behavioural models and their coupling within energy simulation software using a cosimulation approach. The methodology has been applied to a real case study to illustrate its applicability. A one-year monitoring has been carried out through a dedicated sensor network for the data recording and to identify the triggers of users' actions. Then, two stochastic behavioural models (i.e., one for predicting light switching and one for window opening) have been developed (using the measured data) and coupled within the IESVE simulation software. A simplified energy model of the case study has been created to test the behavioural approach. The outcomes highlight that the behavioural approach provides more accurate results than a standard one when compared to real profiles. The adoption of behavioural profiles leads to a reduction of the discrepancy with respect to real profiles up to 58% and 26% when simulating light switching and ventilation, respectively, in comparison to standard profiles. Using data-driven techniques to include the human component in the simulation processes would lead to better predictions both in terms of energy use and occupants' comfort sensations. These aspects can be also included in building control processes (e.g., building management systems) to enhance the environmental and system management