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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Pipelining broadcasts on heterogeneous platforms
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Pipelining broadcasts on heterogeneous platforms

机译：在异构平台上流水线广播

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摘要

In this paper, we consider the communications involved by the execution of a complex application, deployed on a heterogeneous platform. Such applications extensively use macrocommunication schemes, for example, to broadcast data items. Rather than aiming at minimizing the execution time of a single broadcast, we focus on the steady-state operation. We assume that there is a large number of messages to be broadcast in pipeline fashion, and we aim at maximizing the throughput, i.e., the (rational) number of messages which can be broadcast every time-step. We target heterogeneous platforms, modeled by a graph where resources have different communication and computation speeds. Achieving the best throughput may well require that the target platform is used in totality: we show that neither spanning trees nor DAGs are as powerful as general graphs. We show how to compute the best throughput using linear programming, and how to exhibit a periodic schedule, first when restricting to a DAG, and then when using a general graph. The polynomial compactness of the description comes from the decomposition of the schedule into several broadcast trees that are used concurrently to reach the best throughput. It is important to point out that a concrete scheduling algorithm based upon the steady-state operation is asymptotically optimal, in the class of all possible schedules (not only periodic solutions).
机译：在本文中，我们考虑了部署在异构平台上的复杂应用程序执行所涉及的通信。这样的应用例如广泛地使用宏通信方案来广播数据项。与其着眼于最小化单个广播的执行时间，我们关注的是稳态操作。我们假设有大量消息以流水线方式进行广播，我们的目标是使吞吐量最大化，即每个时间步可以广播的（合理）消息数。我们针对异构平台，以图建模，其中资源具有不同的通信和计算速度。要获得最佳吞吐量，很可能需要整体使用目标平台：我们证明，生成树和DAG都没有一般图强大。我们展示了如何使用线性规划来计算最佳吞吐量，以及如何展示周期性的计划，首先是限制DAG，然后是普通图。描述的多项式紧凑性来自调度分解为多个广播树的过程，这些广播树同时使用以达到最佳吞吐量。重要的是要指出，在所有可能的调度程序（不仅是周期解）的类别中，基于稳态操作的具体调度算法是渐近最优的。

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