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CMV: Clustered Majority Voting Reliability-Aware Task Scheduling for Multicore Real-Time Systems

机译:CMV:用于多核实时系统的群集多数表决可靠性感知任务调度

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This paper proposes a novel reliability-aware hard real-time task scheduling method for multicore systems along with a quantitative reliability model. The proposed method uses a heuristic clustered replication to maintain the desired reliability threshold with both minimum replication overhead and latency increase. It also minimizes intercore communication overhead of tasks. Both single and multiple soft errors are considered in this method. Simulation results showthat the efficiency of our proposed approach improves with larger network-on-chip sizes, higher reliability thresholds, and higher number of tolerating errors. The proposed method achieves near optimal replica overhead (up to 7.3% higher than optimal replica overhead) with up to 2500% time complexity improvement compared to exhaustive exploration. Experimental results also show that the feasibility of the proposed method is higher than the conventional replication method up to 9.3%. All experiments are performed on both synthetic random task graphs and PARSEC real application benchmarks. Obtained task mapping solutions with communication volume reduction and near optimal replica overhead impose negligible latency increase (up to 6.3%) in comparison with the space exploration approach.
机译:本文提出了一种新颖的多核系统可靠性感知硬实时任务调度方法以及定量可靠性模型。所提出的方法使用启发式群集复制来维持所需的可靠性阈值,同时最小化复制开销和等待时间增加。它还最大程度地减少了任务之间的内核间通信开销。此方法同时考虑单个和多个软错误。仿真结果表明,所提出的方法的效率随着更大的片上网络尺寸,更高的可靠性阈值和更大的容错数量而提高。与详尽的探索相比,该方法可实现接近最佳的副本开销(比最佳副本开销高7.3%),并且时间复杂度可提高2500%。实验结果还表明,该方法的可行性比常规复制方法高出9.3%。所有实验均在合成随机任务图和PARSEC实际应用基准上进行。与空间探索方法相比,获得的具有通信量减少和接近最佳副本开销的任务映射解决方案带来的延迟增加可忽略不计(最多6.3%)。

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