Numerous irregular graph datasets, for example social networks or web graphs, may contain
even trillions of edges. Often, their structure changes over time and they have domain …

With the extraordinary growth in parallelism at all system scales driven by multicore
architectures, computing performance is increasingly determined by how efficiently high …

We present a decade of evolution and production experience with Jupiter datacenter
network fabrics. In this period Jupiter has delivered 5x higher speed and capacity, 30 …

Sparsely-gated mixture-of-experts (MoE) has been widely adopted to scale deep learning
models to trillion-plus parameters with fixed computational cost. The algorithmic …

The interconnect is one of the most critical components in large scale computing systems,
and its impact on the performance of applications is going to increase with the system size …

Industry experience indicates that the ability to incrementally expand data centers is
essential. However, existing high-bandwidth network designs have rigid structure that …

We introduce a high-performance cost-effective network topology called Slim Fly that
approaches the theoretically optimal network diameter. Slim Fly is based on graphs that …

Many proposals to scale quantum technology rely on modular or distributed designs
wherein individual quantum processors, called nodes, are linked together to form one large …

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 …

High-performance computing systems are of steadily growing interest to provide new levels
of computational capability for an increasing range of applications. The growing use of and …