Network congestion arising from simultaneous data transfers can be a
significant performance bottleneck for many applications, especially when
network resources are shared by multiple concurrently running jobs. Many
studies have focused on the impact of network congestion on either MPI
performance or I/O performance but the interaction between MPI and I/O
traffic is rarely studied and not well understood. In this paper, we analyze
and characterize the interference between MPI and I/O traffic on fat-tree
networks, highlighting the role of important factors such as message sizes,
communication intervals, and job sizes. We also investigate several strategies
for reducing MPI-I/O interference, and the benefits and tradeoffs of
each approach for different scenarios.
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