  Dragonfly class of networks are considered as promising interconnects for
next-generation supercomputers. While Dragonfly+ networks offer more path
diversity than the original Dragonfly design, they are still prone to
performance variability due to their hierarchical architecture and resource
sharing design. Event-driven network simulators are indispensable tools for
navigating complex system design. In this study, we quantitatively evaluate a
variety of application communication interactions on a 3,456-node Dragonfly+
system by using the CODES toolkit. This study looks at the impact of
communication interference from a user's perspective. Specifically, for a given
application submitted by a user, we examine how this application will behave
with the existing workload running in the system under different job placement
policies. Our simulation study considers hundreds of experiment configurations
including four target applications with representative communication patterns
under a variety of network traffic conditions. Our study shows that intra-job
interference can cause severe performance degradation for
communication-intensive applications. Inter-job interference can generally be
reduced for applications with one-to-one or one-to-many communication patterns
through job isolation. Application with one-to-all communication pattern is
resilient to network interference.
