PREM-Based Optimal Task Segmentation Under Fixed Priority Scheduling
PREM-Based Optimal Task Segmentation Under Fixed Priority Scheduling
复制标题
固定优先级调度下基于PREM的最优任务分割
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
R. Pellizzoni
中科院分区：
文献类型：
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作者：
M. R. Soliman;R. Pellizzoni
最近，大量的工作已经讨论了调度任务组成的一系列的内存阶段，其中代码和数据在主存储器和本地存储器之间移动，和计算阶段，其中执行的任务只基于本地存储器的内容，其关键思想是通过调度一个任务的存储器阶段与其他核心上运行的任务的计算阶段并行，以防止主存储器争用。本文提供了两个主要的贡献：（1）我们提出了一个编译器级的工具，基于LLVM中间表示，自动转换成一个有条件的序列段，包括内存和计算阶段的程序;（2）我们提出了一个算法，以找到最佳的分割决策的任务集调度根据固定优先级的分区计划。我们的评估表明，所提出的框架可以可行地应用到现实的程序，并大大优于基线贪婪的方法。
Recently, a large number of works have discussed scheduling tasks consisting of a sequence of memory phases, where code and data are moved between main memory and local memory, and computation phases, where the task executes based on the content of local memory only; the key idea is to prevent main memory contention by scheduling the memory phase of one task in parallel with computation phases of tasks running on other cores. This paper provides two main contributions: (1) we present a compiler-level tool, based on the LLVM intermediate representation, that automatically converts a program into a conditional sequence of segments comprising memory and computation phases; (2) we propose an algorithm to find optimal segmentation decisions for a task set scheduled according to a fixed-priority partitioned scheme. Our evaluation shows that the proposed framework can be feasibly applied to realistic programs, and vastly overperforms a baseline greedy approach.