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A study of predictable execution models implementation for industrial data-flow applications on a multi-core platform with shared banked memory

机译:具有共享银行存储器的多核平台上工业数据流应用的可预测执行模型实现的研究

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We study the implementation of data-flow applications on multi-core processor with on-chip shared multi-banked memory. Specifically, we consider the Kalray MPPA2 processor and three applications coded using the industrial toolchain SCADE Suite. We focus on the runtime environment assuming global static scheduling, time-triggered and non-preemptive execution of tasks. Our contributions include (i) a technique to implement SCADE applications compliant with execution models inspired by PREMs (PRe-dictable Execution Models), (ii) an exhaustive comparison of three execution models with and without isolation, and finally (iii) guidelines for predictable implementation of a data-flow application on multi-core processors with shared on-chip memory.
机译:我们研究了在芯片共享多银行内存的多核处理器上的数据流应用的实现。具体而言,我们考虑使用工业工具箱Scade Suite编码的Kalray MPPA2处理器和三种应用。假设全局静态调度,时间触发和非抢占的任务执行,我们专注于运行时环境。我们的贡献包括(i)一种技术实现符合按数(可令人可疑的执行模型)的执行模型的何种执行模型的技术,(ii)具有和不隔离的三个执行模型的详尽比较,最后(iii)可预测的指导方针在具有共享片上存储器的多核处理器上实现数据流应用。

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