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Can I read Mars: Near-Optimal Throughput with Shallow Buffers in Reconfigurable Datacenter Networks on EtoBox?
Mars: Near-Optimal Throughput with Shallow Buffers in Reconfigurable Datacenter Networks by Vamsi Addanki; Chen Avin; Stefan Schmid is a Computer Science article available to read on EtoBox.
What is Mars: Near-Optimal Throughput with Shallow Buffers in Reconfigurable Datacenter Networks about?
The performance of large-scale computing systems often critically depends on high-performance communication networks. Dynamically reconfigurable topologies, e.g., based on optical circuit switches, are emerging as an innovative new technology to deal with the explosive growth of datacenter traffic. Specifically, periodic reconfigurable datacenter networks (RDCNs) such as RotorNet (SIGCOMM 2017), Opera (NSDI 2020) and Sirius (SIGCOMM 2020) have been shown to provide high throughput, by emulating a complete graph through fast periodic circuit switch scheduling. However, to achieve such a high throughput, existing reconfigurable network designs pay a high price: in terms of potentially high delays, but also, as we show as a first contribution in this paper, in terms of the high buffer requirements. In particular, we show that under buffer constraints, emulating the high-throughput complete graph is infeasible at scale, and we uncover a spectrum of unvisited and attractive alternative RDCNs, which emulate regular graphs, but with lower node degree than the complete graph. We present Mars, a periodic reconfigurable topology which emulates a d-regular graph with near-optimal throughput.
Who reads Mars: Near-Optimal Throughput with Shallow Buffers in Reconfigurable Datacenter Networks?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Vamsi Addanki; Chen Avin; Stefan Schmid
- Publisher
- ACM
- Published
- 2023
- Language
- EN
- Field
- Computer Science (Physical Sciences)