57 research outputs found
Schedulability Analysis for Directed Acyclic Graphs on Multiprocessor Systems at a Subtask Level
International audienceThis paper addresses the problem of scheduling parallel real- time tasks of Directed Acyclic Graph (DAG) model on multiprocessor systems. We propose a new scheduling method based on a subtask-level, which means that the schedulability decisions are taken based on the local temporal parameters of subtasks. This method requires modifying the subtasks to add more parameters which are necessary for the analysis, such as local offsets, deadlines and release jitters. Then we provide interference and workload analyses of DAG tasks, and we provide a schedulability test for any work conserving scheduling algorithm
Global EDF scheduling of directed acyclic graphs on multiprocessor systems
International audienceIn this paper, we study the problem of real-time scheduling of parallel tasks represented by a Directed Acyclic Graph (DAG) on multiprocessor architectures. We focus on Global Earliest Deadline First scheduling of sporadic DAG tasksets with constrained-deadlines on a system of homogeneous processors. Our contributions consist in analyzing DAG tasks by considering their internal structures and providing a tighter bound on the workload and interference analysis. This approach consists in assigning a local offset and deadline for each subtask in the DAG. We derive an improved sufficient schedulability test w.r.t. an existing test proposed in the state of the art. Then we discuss the sustainability of this test
An Experimental Analysis of DAG Scheduling Methods in Hard Real-time Multiprocessor Systems
International audienceThe scheduling of real-time parallel tasks on multiprocessor systems is more complicated than the one of independent sequential tasks, specially for the Directed Acyclic Graph (DAG) parallel model. The complexity is due to the structure of the DAG tasks and the precedence constraints between their subtasks. The trivial DAG scheduling method is to apply directly common real-time scheduling algorithms despite their lack of compatibility with the parallel model. Another scheduling method called the stretching method is summarized as converting each parallel DAG task in the set into a collection of independent sequential threads that are easier to be scheduled. In this paper, we are interested in analyzing global preemptive scheduling of DAGs using both methods by showing that both methods are not comparable in the case of using Deadline Monotonic (DM) and Earliest Deadline First (EDF) scheduling algorithms. Then we use extensive simulations to compare and analyze their performance
A C-DAG task model for scheduling complex real-time tasks on heterogeneous platforms: preemption matters
Recent commercial hardware platforms for embedded real-time systems feature
heterogeneous processing units and computing accelerators on the same
System-on-Chip. When designing complex real-time application for such
architectures, the designer needs to make a number of difficult choices: on
which processor should a certain task be implemented? Should a component be
implemented in parallel or sequentially? These choices may have a great impact
on feasibility, as the difference in the processor internal architectures
impact on the tasks' execution time and preemption cost. To help the designer
explore the wide space of design choices and tune the scheduling parameters, in
this paper we propose a novel real-time application model, called C-DAG,
specifically conceived for heterogeneous platforms. A C-DAG allows to specify
alternative implementations of the same component of an application for
different processing engines to be selected off-line, as well as conditional
branches to model if-then-else statements to be selected at run-time. We also
propose a schedulability analysis for the C-DAG model and a heuristic
allocation algorithm so that all deadlines are respected. Our analysis takes
into account the cost of preempting a task, which can be non-negligible on
certain processors. We demonstrate the effectiveness of our approach on a large
set of synthetic experiments by comparing with state of the art algorithms in
the literature
YARTISS: A Generic, Modular and Energy-Aware Scheduling Simulator for Real-Time Multiprocessor Systems
In this report, we present a free software written in Java, YARTISS, which is a real-time multiprocessor scheduling simulator. It is aimed at comparing user-customized algorithms with ones from the literature on real-time scheduling. This simulator is designed as an easy-to-use modular tool in which new modules can be added without the need to decompress, edit nor recompile existing parts. It can sim-ulate the execution of a large number of concurrent periodic independent tasksets on multiprocessor platforms and generate clear visual results of the scheduling process (both schedules and tunable metrics presentations). Other task models are already implemented in the simulator, like graph tasks with precedence constraints and it is easily extensible to other task models. Moreover, YARTISS can simulate tasksets in which energy consumption is a scheduling parameter in the same manner as Worst Case Execution Time (WCET)
k2U: A General Framework from k-Point Effective Schedulability Analysis to Utilization-Based Tests
To deal with a large variety of workloads in different application domains in
real-time embedded systems, a number of expressive task models have been
developed. For each individual task model, researchers tend to develop
different types of techniques for deriving schedulability tests with different
computation complexity and performance. In this paper, we present a general
schedulability analysis framework, namely the k2U framework, that can be
potentially applied to analyze a large set of real-time task models under any
fixed-priority scheduling algorithm, on both uniprocessor and multiprocessor
scheduling. The key to k2U is a k-point effective schedulability test, which
can be viewed as a "blackbox" interface. For any task model, if a corresponding
k-point effective schedulability test can be constructed, then a sufficient
utilization-based test can be automatically derived. We show the generality of
k2U by applying it to different task models, which results in new and improved
tests compared to the state-of-the-art.
Analogously, a similar concept by testing only k points with a different
formulation has been studied by us in another framework, called k2Q, which
provides quadratic bounds or utilization bounds based on a different
formulation of schedulability test. With the quadratic and hyperbolic forms,
k2Q and k2U frameworks can be used to provide many quantitive features to be
measured, like the total utilization bounds, speed-up factors, etc., not only
for uniprocessor scheduling but also for multiprocessor scheduling. These
frameworks can be viewed as a "blackbox" interface for schedulability tests and
response-time analysis
MCFlow: Middleware for Mixed-Criticality Distributed Real-Time Systems
Traditional fixed-priority scheduling analysis for periodic/sporadic task sets is based on the assumption that all tasks are equally critical to the correct operation of the system. Therefore, every task has to be schedulable under the scheduling policy, and estimates of tasks\u27 worst case execution times must be conservative in case a task runs longer than is usual. To address the significant under-utilization of a system\u27s resources under normal operating conditions that can arise from these assumptions, several \emph{mixed-criticality scheduling} approaches have been proposed. However, to date there has been no quantitative comparison of system schedulability or run-time overhead for the different approaches. In this dissertation, we present what is to our knowledge the first side-by-side implementation and evaluation of those approaches, for periodic and sporadic mixed-criticality tasks on uniprocessor or distributed systems, under a mixed-criticality scheduling model that is common to all these approaches. To make a fair evaluation of mixed-criticality scheduling, we also address some previously open issues and propose modifications to improve schedulability and correctness of particular approaches. To facilitate the development and evaluation of mixed-criticality applications, we have designed and developed a distributed real-time middleware, called MCFlow, for mixed-criticality end-to-end tasks running on multi-core platforms. The research presented in this dissertation provides the following contributions to the state of the art in real-time middleware: (1) an efficient component model through which dependent subtask graphs can be configured flexibly for execution within a single core, across cores of a common host, or spanning multiple hosts; (2) support for optimizations to inter-component communication to reduce data copying without sacrificing the ability to execute subtasks in parallel; (3) a strict separation of timing and functional concerns so that they can be configured independently; (4) an event dispatching architecture that uses lock free algorithms where possible to reduce memory contention, CPU context switching, and priority inversion; and (5) empirical evaluations of MCFlow itself and of different mixed criticality scheduling approaches both with a single host and end-to-end across multiple hosts. The results of our evaluation show that in terms of basic distributed real-time behavior MCFlow performs comparably to the state of the art TAO real-time object request broker when only one core is used and outperforms TAO when multiple cores are involved. We also identify and categorize different use cases under which different mixed criticality scheduling approaches are preferable
Generalized Extraction of Real-Time Parameters for Homogeneous Synchronous Dataflow Graphs
23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2015). 4 to 6, Mar, 2015. Turku, Finland.Many embedded multi-core systems incorporate both dataflow applications with timing constraints and traditional
real-time applications. Applying real-time scheduling techniques on such systems provides real-time guarantees
that all running applications will execute safely without violating their deadlines. However, to apply traditional realtime
scheduling techniques on such mixed systems, a unified model to represent both types of applications
running on the system is required. Several earlier works have addressed this problem and solutions have been
proposed that address acyclic graphs, implicit-deadline models or are able to extract timing parameters
considering specific scheduling algorithms. In this paper, we present an algorithm for extracting real-time
parameters (offsets, deadlines and periods) that are independent of the schedulability analysis, other applications
running in the system, and the specific platform. The proposed algorithm: 1) enables applying traditional real-time
schedulers and analysis techniques on cyclic or acyclic Homogeneous Synchronous Dataflow (HSDF) applications
with periodic sources, 2) captures overlapping iterations, which is a main characteristic of the execution of
dataflow applications, 3) provides a method to assign offsets and individual deadlines for HSDF actors, and 4) is
compatible with widely used deadline assignment techniques, such as NORM and PURE. The paper proves the
correctness of the proposed algorithm through formal proofs and examples
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