Xpander: Unveiling the secrets of high-performance datacenters

Many architectures for high-performance datacenters have been proposed. Surprisingly, recent studies show that datacenter designs with random network topologies outperform more sophisticated designs, achieving near-optimal throughput and bisection bandwidth, high resiliency to failures, incremental expandability, high cost efficiency, and more. Unfortunately, the inherent unstructuredness and unpredictability of random designs pose serious, arguably insurmountable, obstacles to their adoption in practice. Can these guarantees be achieved by well-structured, deterministic datacenters? We provide a surprising affirmative answer. We show, through a combination of theoretical analyses, extensive simulations, and experiments with a network emulator, that any "expander" network topology (as indeed are random graphs) comes with these benefits. We leverage this insight to present Xpander, a novel deterministic datacenter architecture that achieves all of the above desiderata while providing a tangible alternative to existing datacenter designs. We discuss challenges en route to deploying Xpander (including physical layout, cabling costs and complexity, backwards compatibility) and explain how these can be resolved.