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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Rapid Calculation of Max-Min Fair Rates for Multi-Commodity Flows in Fat-Tree Networks
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Rapid Calculation of Max-Min Fair Rates for Multi-Commodity Flows in Fat-Tree Networks

机译：胖树网络中多商品流最大最小公平汇率的快速计算

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摘要

Max-min fairness is often used in the performance modeling of interconnection networks. Existing methods to compute max-min fair rates for multi-commodity flows have high complexity and are computationally infeasible for large networks. In this work, we show that by considering topological features, this problem can be solved efficiently for the fat-tree topology that is widely used in data centers and high performance compute clusters. Several efficient new algorithms are developed for this problem, including a parallel algorithm that can take advantage of multi-core and shared-memory architectures. Using these algorithms, we demonstrate that it is possible to find the max-min fair rate allocation for multi-commodity flows in fat-tree networks that support tens of thousands of nodes. We evaluate the run-time performance of the proposed algorithms and show improvement in orders of magnitude over the previously best known method. We further demonstrate a new application of max-min fair rate allocation that is only computationally feasible using our new algorithms.
机译：互连网络的性能建模中经常使用最大-最小公平性。现有的用于计算多商品流的最大-最小公平汇率的方法具有很高的复杂度，并且对于大型网络在计算上是不可行的。在这项工作中，我们表明通过考虑拓扑特征，对于在数据中心和高性能计算集群中广泛使用的胖树拓扑可以有效地解决此问题。针对此问题开发了几种有效的新算法，包括可以利用多核和共享内存体系结构的并行算法。使用这些算法，我们证明了有可能在支持成千上万个节点的胖树网络中找到多商品流的最大-最小公平速率分配。我们评估了所提出算法的运行时性能，并显示出比以前最知名的方法改进了几个数量级。我们进一步演示了最大-最小公平汇率分配的新应用，该应用只能使用我们的新算法在计算上可行。

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