To meet the increasing demands of parallel scientific applications, supercomputers continue to grow in both scale and complexity. The fastest supercomputer in the world, El Capitan, features over a million CPU cores and tens of thousands of GPUs. Applications running on such large-scale systems are particularly susceptible to system noise or interference caused by the operating system (OS) and other services running on the same compute nodes as the application.

As the US Department of Energy (DOE) computing facilities began deploying petascale systems in 2008, DOE was already setting its sights on exascale. In that year, DARPA published a report on the feasibility of reaching exascale. The report authors identified several key challenges in the pursuit of exascale including power, memory, concurrency, and resiliency. That report informed the DOE's computing strategy for reaching exascale. With the deployment of Oak Ridge National Laboratory's Frontier supercomputer, we have officially entered the exascale era. In this paper, we discuss Frontier's architecture, how it addresses those challenges, and describe some early application results from Oak Ridge Leadership Computing Facility's Center of Excellence and the Exascale Computing Project.

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. In this paper, we will describe SLINGSHOT, an interconnection network for large scale computing systems. SLINGSHOT is based on high-radix switches, which allow building exascale and hyper-scale datacenters networks with at most three switch-to-switch hops. Moreover, SLINGSHOT provides efficient adaptive routing and congestion control algorithms, and highly tunable traffic classes. SLINGSHOT uses an optimized Ethernet protocol, which allows it to be interoperable with standard Ethernet devices while providing high performance to HPC applications. We analyze the extent to which SLINGSHOT provides these features, evaluating it on microbenchmarks and on several applications from the datacenter and AI worlds, as well as on HPC applications. We find that applications running on SLINGSHOT are less affected by congestion compared to previous generation networks.