This study examined the interplay among processor speed, cluster interconnect and file I/O, using parallel applications to quantify interactions. We focused on a common case where multiple compute nodes communicate with a single master node for file accesses. We constructed a predictive model that used time characteristics critical for application performance to estimate the number of nodes beyond which further performance improvement became unattainable. Predictions were experimentally validated with NAMD, a representative parallel application designed for molecular dynamics simulation. Such predictions can help guide decision making to improve machine allocations for parallel codes in large clusters.