Helios: a hybrid electrical/optical switch architecture for modular data centers
Proceedings of the ACM SIGCOMM 2010 conference
SQUID: a practical 100% throughput scheduler for crosspoint buffered switches
IEEE/ACM Transactions on Networking (TON)
USENIXATC'11 Proceedings of the 2011 USENIX conference on USENIX annual technical conference
HotCloud'11 Proceedings of the 3rd USENIX conference on Hot topics in cloud computing
Hey, you darned counters!: get off my ASIC!
Proceedings of the first workshop on Hot topics in software defined networks
PAST: scalable ethernet for data centers
Proceedings of the 8th international conference on Emerging networking experiments and technologies
Data Center Switch for Load Balanced Fat-Trees
Journal of Signal Processing Systems
B4: experience with a globally-deployed software defined wan
Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM
Optimal networks from error correcting codes
ANCS '13 Proceedings of the ninth ACM/IEEE symposium on Architectures for networking and communications systems
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Today, data center networks that scale to tens of thousands of ports require the use of highly-specialized ASICs, with correspondingly high development costs. Simultaneously, these networks also face significant performance and management limitations. Just as commodity processors and disks now form the basis of computing and storage in the data center, we argue that there is an opportunity to leverage emerging high-speed commodity merchant switch silicon as the basis for a scalable, cost-effective, modular, and more manageable data center network fabric. This paper describes how to save cost and power by repackaging an entire data center network as a distributed multi-stage switch using a fat-tree topology and merchant silicon instead of proprietary ASICs. Compared to a fat tree of discrete packet switches, a 3,456-port 10 Gigabit Ethernet realization of our architecture costs 52% less, consumes 31% less power, occupies 84% less space, and reduces the number of long, cumbersome cables from 6,912 down to 96, relative to existing approaches.