Input/Output is a big obstacle to effective use of tenflopsscale computing systems, Motivated by earlier parallel I/O meaurements on an Intel TFLOPS machine, we conduct studies to determine the sensitivity of parallel I/O performance on multi-progmmmed mesh-connected machines with respect to number of I/O nodes, number of compute nodes, network link bandwidth, I/O node bandwidth, spatial layout of jobs, and read or write demands of applications.Our extensive simulations and analytical modeling yield important insights into the limitations on parallel I/O performance due to network contention, and into the possible gains in parallel I/O performance that can be achieved by tuning the spatial layout of jobs.Applying these results, we devise a new processor allocation strategy that is sensitive to parallel I/O traffic and the resulting network contention.In performance evaluations driven by synthetic workloads and by a real workload trace captured at the San Diego Supercomputing Center, the new strategy improves the average response time of parallel I/O intensive jobs by up to a factor of 4.5.
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