Modeling Mixed-critical Systems in Real-time BIP

International audienceThe proliferation of multi- and manycores creates an important design problem: the design and verification for mixed-criticality constraints in timing and safety, taking into account the resource sharing and hardware faults. In our work, we aim to contribute towards the solution of these problems by using a formal design language - the real time BIP, to model both hardware and software, functionality and scheduling. In this paper we present the initial experiments of modeling mixed-criticality systems in BIP

Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions

In the past decade, Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance in various Artificial Intelligence tasks. To accelerate the experimentation and development of CNNs, several software frameworks have been released, primarily targeting power-hungry CPUs and GPUs. In this context, reconfigurable hardware in the form of FPGAs constitutes a potential alternative platform that can be integrated in the existing deep learning ecosystem to provide a tunable balance between performance, power consumption and programmability. In this paper, a survey of the existing CNN-to-FPGA toolflows is presented, comprising a comparative study of their key characteristics which include the supported applications, architectural choices, design space exploration methods and achieved performance. Moreover, major challenges and objectives introduced by the latest trends in CNN algorithmic research are identified and presented. Finally, a uniform evaluation methodology is proposed, aiming at the comprehensive, complete and in-depth evaluation of CNN-to-FPGA toolflows.Comment: Accepted for publication at the ACM Computing Surveys (CSUR) journal, 201

Virtual Node - To Achieve Temporal Isolation and Predictable Integration of Real-Time Components

We present an approach of two-level deployment process for component models used in distributed real-time embedded systems to achieve predictable integration of real-time components. Our main emphasis is on the new concept of virtual node with the use of a hierarchical scheduling technique. Virtual nodes are used as means to achieve predictable integration of software components with real-time requirements. The hierarchical scheduling framework is used to achieve temporal isolation between components (or sets of components). Our approach permits detailed analysis, e.g., with respect to timing, of virtual nodes and this analysis is also reusable with the reuse of virtual nodes. Hence virtual node preserves real-time properties across reuse and integration in different contexts