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Proceedings ArticleDOI

REWIRE: An optimization-based framework for unstructured data center network design

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TLDR
A data center network design framework, that is called REWIRE, to design networks using an optimization algorithm, which significantly outperforms previous solutions and has up to 100-500% more bisection bandwidth and less end-to-end network latency than equivalent-cost DCNs built with best practices.
Abstract
Despite the many proposals for data center network (DCN) architectures, designing a DCN remains challenging. DCN design is especially difficult when expanding an existing network, because traditional DCN design places strict constraints on the topology (e.g., a fat-tree). Recent advances in routing protocols allow data center servers to fully utilize arbitrary networks, so there is no need to require restricted, regular topologies in the data center. Therefore, we propose a data center network design framework, that we call REWIRE, to design networks using an optimization algorithm. Our algorithm finds a network with maximal bisection bandwidth and minimal end-to-end latency while meeting user-defined constraints and accurately modeling the predicted cost of the network. We evaluate REWIRE on a wide range of inputs and find that it significantly outperforms previous solutions—its network designs have up to 100–500% more bisection bandwidth and less end-to-end network latency than equivalent-cost DCNs built with best practices.

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Citations
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Minimizing Communication in All-Pairs Shortest Paths

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References
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Journal ArticleDOI

Optimization by Simulated Annealing

TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Journal ArticleDOI

Introduction to algorithms: 4. Turtle graphics

TL;DR: In this article, a language similar to logo is used to draw geometric pictures using this language and programs are developed to draw geometrical pictures using it, which is similar to the one we use in this paper.
Proceedings ArticleDOI

Dryad: distributed data-parallel programs from sequential building blocks

TL;DR: The Dryad execution engine handles all the difficult problems of creating a large distributed, concurrent application: scheduling the use of computers and their CPUs, recovering from communication or computer failures, and transporting data between vertices.
Proceedings ArticleDOI

VL2: a scalable and flexible data center network

TL;DR: VL2 is a practical network architecture that scales to support huge data centers with uniform high capacity between servers, performance isolation between services, and Ethernet layer-2 semantics, and is built on a working prototype.
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