271 research outputs found
A framework for hierarchical scheduling on multiprocessors: from application requirements to run-time allocation
Hierarchical scheduling is a promising methodology for designing and deploying real-time applications, since it enables component-based design and analysis, and supports temporal isolation among competing applications. In hierarchical scheduling an application is described by means of a temporal interface. The designer faces the problem of how to derive the interface parameters so to make the application schedulable, at the same time minimizing the waste of computational resources. The problem is particularly relevant in multiprocessor systems, where it is not clear yet how the interface parameters influence the schedulability of the application and allocation on the physical platform.
In this paper we present three novel contributions to hierarchical scheduling for multiprocessor systems. First, we propose the Bounded-Delay Multipartition (BDM), a new interface specification model that allows the designer to balance resource usage versus flexibility in selecting the virtual platform parameters. Second, we explore the schedulability region of a real-time application on top of a generic virtual platform, and derive the interface parameter. Finally, we propose Fluid Best-Fit, an algorithm that takes advantage of the extra degree of flexibility provided by the BDM to compute the virtual platform parameters and allocate it on the physical platform. The performance of the algorithm is evaluated by simulations
A Framework for Hierarchical Scheduling on Multiprocessors: From Application Requirements to Run-Time Allocation
Hierarchical scheduling is a promising methodology for designing and deploying real-time applications, since it enables component-based design and analysis, and supports temporal isolation among competing applications. In hierarchical scheduling an application is described by means of a temporal interface. The designer faces the problem of how to derive the interface parameters so to make the application schedulable, at the same time minimizing the waste of computational resources. The problem is particularly relevant in multiprocessor systems, where it is not clear yet how the interface parameters influence the schedulability of the application and allocation on the physical platform.
In this paper we present three novel contributions to hierarchical scheduling for multiprocessor systems. First, we propose the Bounded-Delay Multipartition (BDM), a new interface specification model that allows the designer to balance resource usage versus flexibility in selecting the virtual platform parameters. Second, we explore the schedulability region of a real-time application on top of a generic virtual platform, and derive the interface parameter. Finally, we propose Fluid Best-Fit, an algorithm that takes advantage of the extra degree of flexibility provided by the BDM to compute the virtual platform parameters and allocate it on the physical platform. The performance of the algorithm is evaluated by simulations
Context-sensitive Parametric WCET Analysis
In this paper, we propose aWCET analysis that focuses on two aspects. First, it supports contextsensitive hardware and software timing effects, meaning that it is sensitive to the execution history of the program and thus can account for effects like cache persistence, triangular loop, etc. Second, it supports the introduction of parameters in both the software model (e.g. parametric loop bounds) and the hardware model (e.g. number of cache misses). WCET computation by static analysis is traditionally handled by the Implicit Path Enumeration Technique (IPET), using an Integer Linear Program (ILP) that is difficult to resolve parametrically. We suggest an alternative tree-based approach. We define a context-sensitive CFG format to express these effects, and we provide an efficient method to process it, giving a parametric WCET formula. Experimental results show that this new method is significantly faster and more accurate than existing parametric approaches
Parametric Schedulability Analysis of Fixed Priority Real-Time Distributed Systems
Parametric analysis is a powerful tool for designing modern embedded systems,
because it permits to explore the space of design parameters, and to check the
robustness of the system with respect to variations of some uncontrollable
variable. In this paper, we address the problem of parametric schedulability
analysis of distributed real-time systems scheduled by fixed priority. In
particular, we propose two different approaches to parametric analysis: the
first one is a novel technique based on classical schedulability analysis,
whereas the second approach is based on model checking of Parametric Timed
Automata (PTA).
The proposed analytic method extends existing sensitivity analysis for single
processors to the case of a distributed system, supporting preemptive and
non-preemptive scheduling, jitters and unconstrained deadlines. Parametric
Timed Automata are used to model all possible behaviours of a distributed
system, and therefore it is a necessary and sufficient analysis. Both
techniques have been implemented in two software tools, and they have been
compared with classical holistic analysis on two meaningful test cases. The
results show that the analytic method provides results similar to classical
holistic analysis in a very efficient way, whereas the PTA approach is slower
but covers the entire space of solutions.Comment: Submitted to ECRTS 2013 (http://ecrts.eit.uni-kl.de/ecrts13
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
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