Mixed Critical Earliest Deadline First

International audienceUsing the advances of the modern microelectronics technology, the safety-critical systems, such as avionics, can reduce their costs by integrating multiple tasks on one device. This makes such systems essentially mixed-critical, as this brings together different tasks whose safety assurance requirements may differ significantly. In the context of mixed-critical scheduling theory, we studied the dual criticality problem of scheduling a finite set of hard real-time jobs. In this work we propose an algorithm which is proved to dominate OCBP, a state-of-the art algorithm for this problem that is optimal over fixed job priority algorithms. We show through empirical studies that our algorithm can reduce the set of non-schedulable instances by a factor of two or, under certain assumptions, by a factor of four, when compared to OCBP

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

Multiprocessor Scheduling of Precedence-constrained Mixed-Critical Jobs

International audienceThe real-time system design targeting multiprocessor platforms leads to two important complications in real-time scheduling. First, to ensure deterministic processing by communicating tasks the scheduling has to consider precedence constraints. The second complication factor is mixed criticality, i.e., integration upon a single platform of various subsystems where some are safety-critical (e.g., car braking system) and the others are not (e.g., car digital radio). Therefore we motivate and study the multiprocessor scheduling problem of a finite set of precedence-related mixed criticality jobs. This problem, to our knowledge, has never been studied if not under very specific assumptions. The main contribution of our work is an algorithm that, given a global fixed-priority assignment for jobs, can modify it in order to improve its schedulability for mixed-criticality setting. Our experiments show an increase of schedulable instances up to a maximum of 25% if compared to classical solutions for this category of scheduling problems

A Timed-Automata Based Middleware for Time-Critical Multicore Applications

International audienceThe goal of our work is to contribute to unification of design methodologies for multi-core time-critical systems. Various models of computation have been proposed in literature for this kind of systems, but lack of coherency between them makes unified coherent design methodology challenging. In addition, there is a significant gap between the models of computation and the real-time scheduling and analysis techniques. To overcome this difficulty, we represent both the models of computation and the scheduling policies by timed automata. While, traditionally, they are only used for simulation and validation, we use the automata for programming. We believe that using the same formal language for different design styles and methods is an important step to close the gap between them. Our approach is demonstrated using a publicly available toolset, an industrial application use case and a multi-core platform

Models for Deterministic Execution of Real-Time Multiprocessor Applications

International audienceWith the proliferation of multi-cores in embedded real-time systems, many industrial applications are being (re-)targeted to multiprocessor platforms. However, exactly reproducible data values at the outputs as function of the data and timing of the inputs is less trivial to realize in multiprocessors, while it can be imperative for various practical reasons. Also for parallel platforms it is harder to evaluate the task utilization and ensure schedulability, especially for end-to-end communication timing constraints and aperiodic events. Based upon reactive system extensions of Kahn process networks, we propose a model of computation that employs synchronous events and event priority relations to ensure deterministic execution. For this model, we propose an online scheduling policy and establish a link to a well-developed scheduling theory. We also implement this model in publicly available prototype tools and evaluate them on state-of-the art multi-core hardware, with a streaming benchmark and an avionics case study

SPDF: A Schedulable Parametric Data-Flow MoC (Extended Version)

Dataflow programming models are suitable to express multi-core streaming applications. The design of high-quality embedded systems in that context requires static analysis to ensure the liveness and bounded memory of the application. However, many streaming applications have a dynamic behavior. The previously proposed dataflow models for dynamic applications do not provide any static guarantees or only in exchange of significant restrictions in expressive power or automation. To overcome these restrictions, we propose the schedulable parametric dataflow (SPDF) model of computation. We present static analyses and a quasi-static scheduling algorithm. We demonstrate our approach using a video decoder case study

Many-Core Scheduling of Data Parallel Applications Using SMT Solvers

Abstract—To program recently developed many-core systems-on-chip two traditionally separate performance optimization problems have to be solved together. Firstly, it is the parallel scheduling on a shared-memory multi-core system. Secondly, it is the co-scheduling of network communication and processor computation. This is because many-core systems are networks of multi-core clusters. In this paper, we demonstrate the applicabil-ity of modern constraint solvers to efficiently schedule parallel applications on many-cores and validate the results by running benchmarks on a real many-core platform. Index Terms—task graph, scheduling, multiprocessor, DMA I

Chapter 4 DATAFLOW ANALYSIS FOR REAL-TIME EMBEDDED MULTIPROCESSOR SYSTEM DESIGN

Keywords: Dataflow analysis techniques are key to reduce the number of design iterations and shorten the design time of real-time embedded network based multiprocessor systems that process data streams. With these analysis techniques the worstcase end-to-end temporal behavior of hard real-time applications can be derived from a dataflow model in which computation, communication and arbitration is modeled. For soft real-time applications these static dataflow analysis techniques are combined with simulation of the dataflow model to test statistical assertions about their temporal behavior. The simulation results in combination with properties of the dataflow model are used to derive the sensitivity of design parameters and to estimate parameters like the capacity of data buffers. real-time, dataflow analysis, multiprocessor system, predictable design, systemon-chip 1

SPDF: A Schedulable Parametric DataFlow MoC

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A Statically Analyzable Dataflow Model for Dynamic Streaming

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