Contention-Aware Scheduling with Task Duplication

Sinnen, Oliver; To, Andrea; Kaur, Manpreet

doi:10.1007/978-3-642-04633-9_9

Cited by 12 publications

(13 citation statements)

References 14 publications

(16 reference statements)

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“…Sinnen et al [32] propose a contention-aware scheduling algorithm (the CA-D algorithm: Contention Aware task Duplication) with task duplication. In contention aware scheduling, there is contention for communication resources.…”

Section: An Overview Of the Task Scheduling Algorithms For Multiprocementioning

confidence: 99%

A Randomized Scheduling Algorithm for Multiprocessor Environments Using Local Search

Mishra

2016

Parallel Process. Lett.

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The LOCAL(A, B) randomized task scheduling algorithm is proposed for fully connected multiprocessors. It combines two given task scheduling algorithms (A, and B) using local neighborhood search to give a hybrid of the two given algorithms. Objective is to show that such type of hybridization can give much better performance results in terms of parallel execution times. Two task scheduling algorithms are selected: DSC (Dominant Sequence Clustering as algorithm A), and CPPS (Cluster Pair Priority Scheduling as algorithm B) and a hybrid is created (the LOCAL(DSC, CP P S) or simply the LOCAL task scheduling algorithm). The LOCAL task scheduling algorithm has time complexity O(|V ||E|(|V | + |E|)), where V is the set of vertices, and E is the set of edges in the task graph. The LOCAL task scheduling algorithm is compared with six other algorithms: CPPS, DCCL (Dynamic Computation Communication Load ), DSC, EZ (Edge Zeroing), LC (Linear Clustering), and RDCC (Randomized Dynamic Computation Communication). Performance evaluation of the LOCAL task scheduling algorithm shows that it gives up to 80.47 % improvement of NSL (Normalized Schedule Length) over other algorithms.

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Section: An Overview Of the Task Scheduling Algorithms For Multiprocementioning

confidence: 99%

A Randomized Scheduling Algorithm for Multiprocessor Environments Using Local Search

Mishra

2016

Parallel Process. Lett.

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“…Contention-aware scheduling in computer clusters is extensively studied in [4], [34], and [35]. Scheduling models are proposed considering the contention for communication resources, and list scheduling-based heuristic algorithms are designed to address contention-aware scheduling on heterogeneous machines.…”

Section: Related Workmentioning

confidence: 99%

Application Mapping and Scheduling for Network-on-Chip-Based Multiprocessor System-on-Chip With Fine-Grain Communication Optimization

Yang

Liu

Jiang

et al. 2016

IEEE Trans. VLSI Syst.

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Network-on-chip (NoC) is promising for the communication paradigm of the next-generation multiprocessor system-on-chip (MPSoC). As communication has become an integral part of on-chip computing, and even the performance bottleneck, researchers are paying much attention to its implementation and optimization. Traditional techniques that model communication inaccurately will lead to unexpected runtime performance, which is on average 90.8% worse than the predicted results based on observation, and are not suitable for the deep optimization of communication-intensive scenarios. In this paper, techniques are presented for the NoC-based MPSoCs that integrate optimization on interprocessor communications with the objective of minimizing the schedule length. A fine-grained integer-linear programming (ILP) model is proposed to properly address the communication latency with a network contention, which generates runtime scheduling with trivial performance difference from the predictions. We further propose a heuristic algorithm, unified priority-based scheduling (UPS), to effectively solve the contention problem in polynomial time by assigning priorities to messages. Evaluation results show that the solutions obtained by the ILP model outperform the state-of-the-art techniques by 31.1%, and UPS improves application performance by 34.7% and 44.4% compared with acquainted first-in-first-out (FIFO)-based and random-based methods. In addition, UPS achieves averagely 8.3% approximated results with the optimal solutions generated by ILP. A case study on H.264 high-definition television (HDTV) decoder and the digital signal processor (DSP) filter benchmarks achieves significant improvement on the performance and the results prediction accuracy, as well as the prominent reduction in the number of network contention and energy consumption.

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“…Cosnard et al [11,12] studied the compact representation and symbolic scheduling of DAGs to avoid the unrolling of dependence structure. Sinnen et al [29] presented scheduling with task duplication under communication contention. Bozdag et al [8] optimized the number of processors required in duplication-based scheduling.…”

Section: Progress In Dag-based Parallelization and Schedulingmentioning

confidence: 99%

Author retrospective for PYRROS

Yang

Gerasoulis

2014

25th Anniversary International Conference on Supercomputing Anniversary Volume -

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Given a program with annotated task parallelism represented as a directed acyclic graph (DAG), the PYRROS project was focused on fast DAG scheduling, code generation and runtime execution on distributed memory architectures. PYRROS scheduling goes through several processing stages including clustering of tasks, cluster mapping, and task execution ordering. Since the publication of the PYRROS project, there have been new advancements in the area of DAG scheduling algorithms, the use of DAG scheduling for irregular and large-scale computation, and software system development with annotated task parallelism on modern parallel and cloud architectures. This retrospective describes our experience from this project and the follow-up work, and reviews representative papers related to DAG scheduling published in the last decade. Original paper: http://dx.

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Contention-Aware Scheduling with Task Duplication

Cited by 12 publications

References 14 publications

A Randomized Scheduling Algorithm for Multiprocessor Environments Using Local Search

A Randomized Scheduling Algorithm for Multiprocessor Environments Using Local Search

Application Mapping and Scheduling for Network-on-Chip-Based Multiprocessor System-on-Chip With Fine-Grain Communication Optimization

Author retrospective for PYRROS

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