Stress resistant scheduling algorithms for CIOQ switches

Prashanth Pappu, J. Turner
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引用次数: 4

Abstract

Practical crossbar scheduling algorithms for CIOQ switches such as PIM and i-SLIP, can perform poorly under extreme traffic conditions, frequently failing to be work-conserving. The common practice of evaluating crossbar scheduling algorithms according to the packet delay under random admissible traffic tends to obscure significant differences that affect the robustness of different algorithms when exposed to extreme conditions. On the other hand, algorithms such as LOOFA with provably good worst-case performance, don't lend themselves readily to high performance implementation. We advocate evaluating crossbar scheduling algorithms using targeted stress tests which seek to probe the performance boundaries of competing alternatives. Appropriately designed stress tests can reveal key-differences among algorithms and can provide the insight needed to spur the development of better solutions. In this paper, we introduce the use of stress testing for crossbar scheduling and use it to evaluate the performance of PIM, i-SLIP and LOOFA. Our results show that PlM and i-SLIP need large speedups in order to perform well on stress tests, while LOOFA can deliver excellent performance, even for speedups less than 1.5. We then develop improved versions of PIM and i-SLIP, which take output queue lengths into account, making them much more robust. We also develop an algorithm which closely approximates the behavior (and performance) of LOOFA, but which admits a straightforward, high performance hardware implementation.
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CIOQ交换机的抗应力调度算法
PIM和i-SLIP等CIOQ交换机的交叉调度算法在极端交通条件下表现不佳,经常不能节省工作。根据随机可接受流量下的数据包延迟评估交叉排程算法的常见做法往往会掩盖在极端条件下影响不同算法鲁棒性的显著差异。另一方面,像LOOFA这样的算法虽然可以证明具有良好的最坏情况性能,但并不容易用于高性能实现。我们提倡使用有针对性的压力测试来评估交叉排程算法,该测试旨在探索竞争替代方案的性能边界。适当设计的压力测试可以揭示算法之间的关键差异,并可以提供刺激开发更好解决方案所需的见解。本文介绍了应力测试在横杆调度中的应用,并用它来评价PIM、i-SLIP和LOOFA的性能。我们的结果表明,PlM和i-SLIP需要较大的加速才能在压力测试中表现良好,而LOOFA即使在小于1.5的加速下也可以提供出色的性能。然后,我们开发了PIM和i-SLIP的改进版本,它们考虑了输出队列长度,使它们更加健壮。我们还开发了一种算法,它非常接近LOOFA的行为(和性能),但它允许一个简单的、高性能的硬件实现。
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