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Reconfigurable datacenter networks use fast optical circuit switches to provide high bandwidths at low cost, therefore emerging as a compelling alternative to packet switching. These switches offer micro- and nano-second reconfiguration, and reacting to demand at this time scale is infeasible. Proposed designs have therefore largely been oblivious, supporting arbitrary traffic patterns. However, this imposes a fundamental latency-throughput tradeoff that significantly limits the benefits of these switches. In this paper, we illustrate the feasibility of semi-oblivious reconfigurable datacenter networks that periodically adapt to large-scale structural patterns in traffic. We argue that such patterns are predictable in modern datacenters, that optimizing for them can provide latency-throughput scaling superior to oblivious designs, and that existing fast circuit-switched technologies support coarse-grained flexibility to adapt to these patterns.
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Cerberus: The Power of Choices in Datacenter Topology Design - A Throughput Perspective
The bandwidth and latency requirements of modern datacenter applications have led researchers to propose various topology designs using static, dynamic demand-oblivious (rotor), and/or dynamic demand-aware switches. However, given the diverse nature of datacenter traffic, there is little consensus about how these designs would fare against each other. In this work, we analyze the throughput of existing topology designs under different traffic patterns and study their unique advantages and potential costs in terms of bandwidth and latency ''tax''. To overcome the identified inefficiencies, we propose Cerberus, a unified, two-layer leaf-spine optical datacenter design with three topology types. Cerberus systematically matches different traffic patterns with their most suitable topology type: e.g., latency-sensitive flows are transmitted via a static topology, all-to-all traffic via a rotor topology, and elephant flows via a demand-aware topology. We show analytically and in simulations that Cerberus can improve throughput significantly compared to alternative approaches and operate datacenters at higher loads while being throughput-proportional.
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- Award ID(s):
- 2107244
- PAR ID:
- 10342569
- Date Published:
- Journal Name:
- Proceedings of the ACM on Measurement and Analysis of Computing Systems
- Volume:
- 5
- Issue:
- 3
- ISSN:
- 2476-1249
- Page Range / eLocation ID:
- 1 to 33
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3491050
