This paper proposes optical network interconnects as a key enabler for building high-
bandwidth ML training clusters with strong scaling properties. Our design, called SiP-ML …

The bandwidth and latency requirements of modern datacenter applications have led
researchers to propose various topology designs using static, dynamic demand-oblivious …

The performance of many cloud-based applications critically depends on the capacity of the
underlying datacenter network. A particularly innovative approach to improve the throughput …

The performance of large-scale computing systems often critically depends on high-
performance communication networks. Dynamically reconfigurable topologies, eg, based on …

Emerging reconfigurable datacenters allow to dynamically adjust the network topology in a
demand-aware manner. These datacenters rely on optical switches which can be …

This paper studies a fundamental algorithmic problem related to the design of demand-
aware networks: networks whose topologies adjust toward the traffic patterns they serve, in …

Reconfigurable optical topologies are a promising new technology to improve datacenter
network performance and cope with the explosive growth of traffic. In particular, these …

We consider the fundamental problem of designing a self-adjusting tree, which efficiently
and locally adapts itself towards the demand it serves (namely accesses to the items stored …

The explosively growing communication traffic in datacenters imposes increasingly stringent
performance requirements on the underlying networks. Over the last years, researchers …

We propose Kevin, a novel demand-aware reconfigurable rack-to-rack datacenter network
realized with a simple and efficient control plane. In particular, Kevin makes effective use of …