Efficient Routing Mechanisms for Dragonfly Networks

García, María Jesús Márquez; Vallejo, Enrique; Beivide, Ramón; Odriozola, M.; Valero, Mateo

doi:10.1109/icpp.2013.72

Cited by 41 publications

(26 citation statements)

References 19 publications

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“…Several routing mechanisms have been proposed for the Dragonfly network [4], [7], [8], [3], [5]. In this work we classify them in three categories: oblivious, source-based adaptive, and in-transit adaptive routing.…”

Section: Routing Mechanismsmentioning

confidence: 99%

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Throughput Unfairness in Dragonfly Networks under Realistic Traffic Patterns

Fuentes

Vallejo

Camarero

et al. 2015

2015 IEEE International Conference on Cluster Computing

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Abstract-Dragonfly networks have a two-level hierarchical arrangement of the network routers, and allow for a competitive cost-performance solution in large systems. Nonminimal adaptive routing is employed to fully exploit the path diversity and increase the performance under adversarial traffic patterns. Throughput unfairness prevents a balanced use of the resources across the network nodes and degrades severely the performance of any application running on an affected node. Previous works have demonstrated the presence of throughput unfairness in Dragonflies under certain adversarial traffic patterns, and proposed different alternatives to effectively combat such effect.In this paper we introduce a new traffic pattern denoted adversarial consecutive (ADVc), which portrays a real use case, and evaluate its impact on network performance and throughput fairness. This traffic pattern is the most adversarial in terms of network fairness. Our evaluations, both with or without transit-over-injection priority, show that global misrouting policies do not properly alleviate this problem. Therefore, explicit fairness mechanisms are required for these networks.

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Section: Routing Mechanismsmentioning

confidence: 99%

“…Throughput unfairness was identified in [3] when employing an adversarial traffic pattern (ADV) that heavily congests one router in every group. A new global misrouting policy named Mixed-mode (MM) was proposed for the selection of the intermediate group in the non-minimal path for in-transit adaptive routing mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Throughput Unfairness in Dragonfly Networks under Realistic Traffic Patterns

Fuentes

Vallejo

Camarero

et al. 2015

2015 IEEE International Conference on Cluster Computing

Self Cite

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show abstract

“…Several routing mechanisms have been proposed for the dragonfly network [19,18,14,11,7]. In this work we classify them in three categories: oblivious, sourcebased adaptive, and in-transit adaptive routing.…”

Section: Routing Mechanismsmentioning

confidence: 99%

“…In-network congestion in dragonflies is typically employed to drive adaptive routing, as implemented in all the adaptive mechanisms in this paper, [19,18,11]. Nonminimal routing is employed in such case to avoid congested areas, and throughput is typically reduced in half due to the use of Valiant routing.…”

Section: Related Workmentioning

confidence: 99%

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Network unfairness in dragonfly topologies

et al. 2016

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Dragonfly networks arrange network routers in a two-level hierarchy, providing a competitive cost-performance solution for large systems. Nonminimal adaptive routing (adaptive misrouting) is employed to fully exploit the path diversity and increase the performance under adversarial traffic patterns. Network fairness issues arise in the dragonfly for several combinations of traffic pattern, global misrouting and traffic prioritization policy. Such unfairness prevents a balanced use of the resources across the network nodes and degrades severely the performance of any application running on an affected node. This paper reviews the main causes behind network unfairness in dragonflies, including a new adversarial traffic pattern which can easily occur in actual systems and congests all the global output links of a single router. A solution for the observed unfairness is evaluated using age-based arbitration. Results show that age-based arbitration mitigates fairness issues especially when using in-transit adaptive routing. However, when using source adaptive routing, the saturation of the new traffic pattern interferes with the mechanisms employed to detect remote congestion, and the problem grows with the network size. This makes source adaptive routing in dragonflies based on remote notifications prone to reduced performance, even when using age-based arbitration.

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Non‐minimal adaptive routing based on explicit congestion notifications

Benito

Vallejo

Izu

et al. 2018

Concurrency and Computation

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Low-diameter networks require non-minimal adaptive routing to deal with varying traffic characteristics and avoid pathological performance. Such routing is based on local estimations of network congestion, based on link-level flow control credits. Dragonfly networks based on the extensions of commodity Ethernet networks using OpenFlow have been proposed for large HPC deployments with low power consumption. However, this network technology does not implement credit-based flow control. This work explores a range of routing solutions based on exploiting explicit congestion notification messages (in particular, 802.1Qau) to adapt the number of packets using non-minimal paths. The design (denoted QCN-Switch) associates a probability value to each output port. This value is updated to reflect downstream congestion and used to statistically divert traffic away from congested areas when the load is uneven, as in the case of adversarial traffic. A feedback comparison variant is designed to separate the cases of uniform traffic at saturation and adversarial traffic at low loads. Evaluation results show that QCN-Switch is a competitive design for both the uniform traffic and adversarial traffic. Furthermore, it is able to react to changes in traffic conditions in 0.4 ms or less. A sensitivity analysis identifies the best configuration and shows its performance trade-offs.

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Efficient Routing Mechanisms for Dragonfly Networks

Cited by 41 publications

References 19 publications

Throughput Unfairness in Dragonfly Networks under Realistic Traffic Patterns

Throughput Unfairness in Dragonfly Networks under Realistic Traffic Patterns

Network unfairness in dragonfly topologies

Non‐minimal adaptive routing based on explicit congestion notifications

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