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Contention-Conscious Transaction Ordering in Multiprocessor DSP Systems

机译:多处理器DSP系统中竞争意识的事务排序

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This paper explores the problem of efficiently ordering interprocessor communication (IPC) operations in statically scheduled multiprocessors for iterative dataflow graphs. In most digital signal processing (DSP) applications, the throughput of the system is significantly affected by communication costs. By explicitly modeling these costs within an effective graph-theoretic analysis framework, we show that ordered transaction schedules can significantly outperform self-timed schedules even when synchronization costs are low. However, we also show that when communication latencies are nonnegligible, finding an optimal transaction order given a static schedule is an NP-complete problem, and that this intractability holds both under iterative and noniterative execution. We develop new heuristics for finding efficient transaction orders, and perform an extensive experimental comparison to gauge the performance of these heuristics.
机译:本文探讨了在静态调度的多处理器中为迭代数据流图有效排序处理器间通信(IPC)操作的问题。在大多数数字信号处理(DSP)应用中,系统的吞吐量受通信成本的影响很大。通过在有效的图论分析框架内对这些成本进行显式建模,我们表明,即使同步成本很低,有序交易计划也可以明显优于自定时计划。但是,我们还表明,当通信等待时间不可忽略时,在给定静态计划的情况下找到最佳交易顺序是一个NP完全问题,并且这种难处理性在迭代和非迭代执行中均成立。我们开发了新的启发式方法以查找有效的交易订单,并进行了广泛的实验比较以评估这些启发式方法的性能。

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