An effective compaction strategy for bi-criteria DAG scheduling in grids
International Journal of Communication Networks and Distributed Systems
Contention-aware scheduling with task duplication
Journal of Parallel and Distributed Computing
Ten thousand SQLs: parallel keyword queries computing
Proceedings of the VLDB Endowment
Optimizing latency and throughput of application workflows on clusters
Parallel Computing
Scheduling tasks and communications on a hierarchical system with message contention
ICA3PP'11 Proceedings of the 11th international conference on Algorithms and architectures for parallel processing - Volume Part II
Scheduling for heterogeneous Systems using constrained critical paths
Parallel Computing
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Many DAG scheduling algorithms generate schedules that require prohibitively large number of processors. To address this problem, we propose a generic algorithm, SC, to minimize the processor requirement of any given valid schedule. SC preserves the schedule length of the original schedule and reduces processor count by merging processor schedules and removing redundant duplicate tasks. To the best of our knowledge, this is the first algorithm to address this highly unexplored aspect of DAG scheduling. Onaverage, SC reduced the processor requirement 91, 82, and 72 percent for schedules generated by PLW, TCSD, and CPFD algorithms, respectively. SC algorithm has a low complexity (O(\vert {\cal N}\vert^3)) compared to most duplication-based algorithms. Moreover, it decouples processor economization from schedule length minimization problem. To take advantage of these features of SC, we also propose a scheduling algorithm SDS, having the same time complexity as SC. Our experiments demonstrate that schedules generated by SDS are only 3 percent longer than CPFD (O(\vert {\cal N}\vert^4)), one of the best algorithms in that respect. SDS and SC together form a two-stage scheduling algorithm that produces schedules with high quality and low processor requirement, and has lower complexity than the comparable algorithms that produce similar high-quality results.