Making formal verification amenable to real-time UML practitioners

TTool, a real-time UML toolkit, offers user-friendly interfaces to formal verification techniques such as reachability analysis, observer-based analysis and automatic generation of traceability matrices. Those techniques are surveyed in the paper

The TASTE Toolset: turning human designed heterogeneous systems into computer built homogeneous software.

The TASTE tool-set results from spin-off studies of the ASSERT project, which started in 2004 with the objective to propose innovative and pragmatic solutions to develop real-time software. One of the primary targets was satellite flight software, but it appeared quickly that their characteristics were shared among various embedded systems. The solutions that we developed now comprise a process and several tools ; the development process is based on the idea that real-time, embedded systems are heterogeneous by nature and that a unique UML-like language was not helping neither their construction, nor their validation. Rather than inventing yet another "ultimate" language, TASTE makes the link between existing and mature technologies such as Simulink, SDL, ASN.1, C, Ada, and generates complete, homogeneous software-based systems that one can straightforwardly download and execute on a physical target. Our current prototype is moving toward a marketed product, and sequel studies are already in place to support, among others, FPGA systems

Test exploration and validation using transaction level models

The complexity of the test infrastructure and test strategies in systems-on-chip approaches the complexity of the functional design space. This paper presents test design space exploration and validation of test strategies and schedules using transaction level models (TLMs). Since many aspects of testing involve the transfer of a significant amount of test stimuli and responses, the communication-centric view of TLMs suits this purpose exceptionally wel

PyCARL: A PyNN Interface for Hardware-Software Co-Simulation of Spiking Neural Network

We present PyCARL, a PyNN-based common Python programming interface for hardware-software co-simulation of spiking neural network (SNN). Through PyCARL, we make the following two key contributions. First, we provide an interface of PyNN to CARLsim, a computationally-efficient, GPU-accelerated and biophysically-detailed SNN simulator. PyCARL facilitates joint development of machine learning models and code sharing between CARLsim and PyNN users, promoting an integrated and larger neuromorphic community. Second, we integrate cycle-accurate models of state-of-the-art neuromorphic hardware such as TrueNorth, Loihi, and DynapSE in PyCARL, to accurately model hardware latencies that delay spikes between communicating neurons and degrade performance. PyCARL allows users to analyze and optimize the performance difference between software-only simulation and hardware-software co-simulation of their machine learning models. We show that system designers can also use PyCARL to perform design-space exploration early in the product development stage, facilitating faster time-to-deployment of neuromorphic products. We evaluate the memory usage and simulation time of PyCARL using functionality tests, synthetic SNNs, and realistic applications. Our results demonstrate that for large SNNs, PyCARL does not lead to any significant overhead compared to CARLsim. We also use PyCARL to analyze these SNNs for a state-of-the-art neuromorphic hardware and demonstrate a significant performance deviation from software-only simulations. PyCARL allows to evaluate and minimize such differences early during model development.Comment: 10 pages, 25 figures. Accepted for publication at International Joint Conference on Neural Networks (IJCNN) 202

From MARTE to dynamically reconfigurable FPGAs : Introduction of a control extension in a model based design flow

System-on-Chip (SoC) can be considered as a particular case of embedded systems and has rapidly became a de-facto solution for implement- ing these complex systems. However, due to the continuous exponential rise in SoC's design complexity, there is a critical need to find new seamless method- ologies and tools to handle the SoC co-design aspects. This paper addresses this issue and proposes a novel SoC co-design methodology based on Model Driven Engineering (MDE) and the MARTE (Modeling and Analysis of Real-Time and Embedded Systems) standard proposed by OMG (Object Management Group), in order to raise the design abstraction levels. Extensions of this standard have enabled us to move from high level specifications to execution platforms such as reconfigurable FPGAs; and allow to implement the notion of Partial Dy- namic Reconfiguration supported by current FPGAs. The overall objective is to carry out system modeling at a high abstraction level expressed in UML (Unified Modeling Language); and afterwards, transform these high level mod- els into detailed enriched lower level models in order to automatically generate the necessary code for final FPGA synthesis

The COMPLEX reference framework for HW/SW co-design and power management supporting platform-based design-space exploration

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UML as a system level design methodology with application to software radio

Master'sMASTER OF SCIENC

Operational Semantics of the Marte Repetitive Structure Modeling Concepts for Data-Parallel Applications Design

International audienceThis paper presents an operational semantics of the repetitive model of computation, which is the basis for the repetitive structure modeling (RSM) package defined in the standard UML Marte profile. It also deals with the semantics of an RSM extension for control-oriented design. The goal of this semantics is to serve as a formal support for i) reasoning about the behavioral properties of models specified in Marte with RSM, and ii) defining correct-by-construction model transformations for the production of executable code in a model-driven engineering framework

A proposed synthesis method for Application-Specific Instruction Set Processors

Due to the rapid technology advancement in integrated circuit era, the need for the high computation performance together with increasing complexity and manufacturing costs has raised the demand for high-performance con fi gurable designs; therefore, the Application-Speci fi c Instruction Set Processors (ASIPs) are widely used in SoC design. The automated generation of software tools for ASIPs is a commonly used technique, but the automated hardware model generation is less frequently applied in terms of fi nal RTL implementations. Contrary to this, the fi nal register-transfer level models are usually created, at least partly, manually. This paper presents a novel approach for automated hardware model generation for ASIPs. The new solution is based on a novel abstract ASIP model and a modeling language (Algorithmic Microarchitecture Description Language, AMDL) optimized for this architecture model. The proposed AMDL-based pre-synthesis method is based on a set of pre-de fi ned VHDL implementation schemes, which ensure the qualities of the automatically generated register-transfer level models in terms of resource requirement and operation frequency. The design framework implementing the algorithms required by the synthesis method is also presented