  Cloud computing represents an appealing opportunity for cost-effective
deployment of HPC workloads on the best-fitting hardware. However, although
cloud and on-premise HPC systems offer similar computational resources, their
network architecture and performance may differ significantly. For example,
these systems use fundamentally different network transport and routing
protocols, which may introduce network noise that can eventually limit the
application scaling. This work analyzes network performance, scalability, and
cost of running HPC workloads on cloud systems. First, we consider latency,
bandwidth, and collective communication patterns in detailed small-scale
measurements, and then we simulate network performance at a larger scale. We
validate our approach on four popular cloud providers and three on-premise HPC
systems, showing that network (and also OS) noise can significantly impact
performance and cost both at small and large scale.
