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Roy Bannon

dblp:166/6963 · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0005-4523-186XORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
2 papers
Datacenter networks · 42% Optical networks · 39% Routing and switching · 10%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Optical networks › optical switching
optical circuit switching
0.712023
Lightwave Fabrics: At-Scale Optical Circuit Switching for Datacenter and Machine Learning Systems · SIGCOMM 2023
Datacenter networks
optical datacenter network
0.712023
Lightwave Fabrics: At-Scale Optical Circuit Switching for Datacenter and Machine Learning Systems · SIGCOMM 2023
Software-defined and programmable networks › control plane
centralized control
0.212015
Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google's Datacenter Network · SIGCOMM 2015
Routing and switching › switching networks › multistage interconnection network
clos network
0.212015
Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google's Datacenter Network · SIGCOMM 2015
Optical networks
wavelength-division multiplexing
0.212023
Lightwave Fabrics: At-Scale Optical Circuit Switching for Datacenter and Machine Learning Systems · SIGCOMM 2023
Datacenter networks
datacenter routing
0.112015
Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google's Datacenter Network · SIGCOMM 2015

Methods — techniques the papers use, named apart from their topics

hardware-software co-design · 0.7
YearPublicationVenuePosition
2023 Lightwave Fabrics: At-Scale Optical Circuit Switching for Datacenter and Machine Learning Systems
abstract
We describe our experience developing what we believe to be the world's first large-scale production deployments of lightwave fabrics used for both datacenter networking and machine-learning (ML) applications. Using optical circuit switches (OCSes) and optical transceivers developed in-house, we employ hardware and software codesign to integrate the fabrics into our network and computing infrastructure. Key to our design is a high degree of multiplexing enabled by new kinds of wavelength-division-multiplexing (WDM) and optical circulators that support high-bandwidth bidirectional traffic on a single strand of optical fiber. The development of the requisite OCS and optical transceiver technologies leads to a synchronous lightwave fabric that is reconfigurable, low latency, rate agnostic, and highly available. These fabrics have provided substantial benefits for long-lived traffic patterns in our datacenter networks and predictable traffic patterns in tightly-coupled machine learning clusters. We report results for a large-scale ML superpod with 4096 tensor processing unit (TPU) V4 chips that has more than one ExaFLOP of computing power. For this use case, the deployment of a lightwave fabric provides up to 3× better system availability and model-dependent performance improvements of up to 3.3× compared to a static fabric, despite constituting less than 6% of the total system cost.
Ryohei Urata, Kevin Yasumura, Roy Bannon, Jill Berger, Pedram Dashti, Norman P. Jouppi, Cedric F. Lam, Sheng Li 0007, Erji Mao, Daniel Nelson, George Papen, Muhammad Mukarram Bin Tariq, Amin Vahdat
SIGCOMM5
2015 Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google's Datacenter Network
abstract
We present our approach for overcoming the cost, operational complexity, and limited scale endemic to datacenter networks a decade ago. Three themes unify the five generations of datacenter networks detailed in this paper. First, multi-stage Clos topologies built from commodity switch silicon can support cost-effective deployment of building-scale networks. Second, much of the general, but complex, decentralized network routing and management protocols supporting arbitrary deployment scenarios were overkill for single-operator, pre-planned datacenter networks. We built a centralized control mechanism based on a global configuration pushed to all datacenter switches. Third, modular hardware design coupled with simple, robust software allowed our design to also support inter-cluster and wide-area networks. Our datacenter networks run at dozens of sites across the planet, scaling in capacity by 100x over ten years to more than 1Pbps of bisection bandwidth.
Joon Ong, Glen Anderson, Ashby Armistead, Roy Bannon, Seb Boving, Gaurav Desai, Bob Felderman, Paulie Germano, Anand Kanagala, Jeff Provost, Jason Simmons, Eiichi Tanda, Jim Wanderer, Urs Hölzle, Stephen Stuart, Amin Vahdat
SIGCOMM6