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Generic algorithms for scheduling applications on heterogeneous platforms

机译:用于在异构平台上调度应用的通用算法

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We study the problem of executing an application represented by a precedence task graph ona parallel machine composed of standard computing cores and accelerators. Both off-line andon-line settings are addressed by proposing generic scheduling approaches. In the first case, weestablish strong lower bounds on the worst-case performance of a known approach based onLinear Programming and replace the greedy List Scheduling policy used in this approach by abetter task ordering. Although this modification leads to the same approximability guarantees,it performs much better in practice. We also extend this algorithm to more types of computingunits, achieving an approximation ratio which depends on the number of different types. In theon-line case, tasks arrive in any order which respects the precedence relations and the schedulerhas to take irrevocable decisions about their allocation and execution.We propose the firston-line scheduling algorithm taking into account precedences, which is based on adequate rulesfor selecting the type of processorwhere to allocate the tasks. Finally, all the previous algorithmshave been experimented on a large number of simulations built on actual libraries, assessing theirgood practical behavior with respect to the state-of-the-art solutions and baseline algorithms.
机译:我们研究了执行优先级任务图表所代表的应用程序的问题由标准计算芯和加速器组成的并联机器。双线和通过提出通用调度方法来解决在线设置。在第一种情况下,我们基于的已知方法的最坏情况性能建立强大的下限线性编程和替换此方法中使用的贪婪列表调度策略更好的任务订购。虽然这种修改导致相同的近似性保证,它在实践中表现得更好。我们还将此算法扩展到更多类型的计算单位,实现近似比取决于不同类型的数量。在里面在线案例,任务以任何尊重优先关系和调度程序的订单到达必须采取关于他们的分配和执行的不可撤销决策。我们提出了第一个考虑到优先级的在线调度算法,基于适用于适用规则用于选择要分配任务的处理程序类型。最后,所有以前的算法已经在实际库上建立了大量模拟,评估其关于最先进的解决方案和基线算法的良好实用行为。

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