89,822 research outputs found
Reservation-Based Federated Scheduling for Parallel Real-Time Tasks
This paper considers the scheduling of parallel real-time tasks with
arbitrary-deadlines. Each job of a parallel task is described as a directed
acyclic graph (DAG). In contrast to prior work in this area, where
decomposition-based scheduling algorithms are proposed based on the
DAG-structure and inter-task interference is analyzed as self-suspending
behavior, this paper generalizes the federated scheduling approach. We propose
a reservation-based algorithm, called reservation-based federated scheduling,
that dominates federated scheduling. We provide general constraints for the
design of such systems and prove that reservation-based federated scheduling
has a constant speedup factor with respect to any optimal DAG task scheduler.
Furthermore, the presented algorithm can be used in conjunction with any
scheduler and scheduling analysis suitable for ordinary arbitrary-deadline
sporadic task sets, i.e., without parallelism
A Graph-Partition-Based Scheduling Policy for Heterogeneous Architectures
In order to improve system performance efficiently, a number of systems
choose to equip multi-core and many-core processors (such as GPUs). Due to
their discrete memory these heterogeneous architectures comprise a distributed
system within a computer. A data-flow programming model is attractive in this
setting for its ease of expressing concurrency. Programmers only need to define
task dependencies without considering how to schedule them on the hardware.
However, mapping the resulting task graph onto hardware efficiently remains a
challenge. In this paper, we propose a graph-partition scheduling policy for
mapping data-flow workloads to heterogeneous hardware. According to our
experiments, our graph-partition-based scheduling achieves comparable
performance to conventional queue-base approaches.Comment: Presented at DATE Friday Workshop on Heterogeneous Architectures and
Design Methods for Embedded Image Systems (HIS 2015) (arXiv:1502.07241
Efficient parallel architecture for highly coupled real-time linear system applications
A systematic procedure is developed for exploiting the parallel constructs of computation in a highly coupled, linear system application. An overall top-down design approach is adopted. Differential equations governing the application under consideration are partitioned into subtasks on the basis of a data flow analysis. The interconnected task units constitute a task graph which has to be computed in every update interval. Multiprocessing concepts utilizing parallel integration algorithms are then applied for efficient task graph execution. A simple scheduling routine is developed to handle task allocation while in the multiprocessor mode. Results of simulation and scheduling are compared on the basis of standard performance indices. Processor timing diagrams are developed on the basis of program output accruing to an optimal set of processors. Basic architectural attributes for implementing the system are discussed together with suggestions for processing element design. Emphasis is placed on flexible architectures capable of accommodating widely varying application specifics
A Maximal Tree Approach For Scheduling Tasks In A Multiprocessor System.
The problem of scheduling tasks across distributed system has been approved to be NP-complete in its general case. When communication cost among system processors is not considered, polynominal-time optimal algorithms for solving scheduling problem are exit only in three special cases. In attempting to solve the problem in the general case, a number of heuristics have been developed. These algorithms intend to reduce the input task graph to one of the special cases and then optimal scheduling can be obtained accordingly. In this paper, we study all these heuristics, and present a improved heuristic --- “Maximal Tree graph approach for scheduling general task graph in the parallel system. A package is developed for comparing the proposed heuristic with three other algorithms, List, Maximal chain and Augmentation. A number of experimental studies have been conducted to compare the proposed technique with these known heuristics. Finally, the conclusion of the algorithm is most efficient for a certain kind of task graph was made accordingly
- …