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In this paper, we present a methodology for profiling parallel applications executing on the IBM PowerXCell 8i (commonly referred to as the ldquoCellrdquo processor). Specifically, we examine Cell-centric MPI programs on hybrid clusters containing multiple Opteron and Cell processors per node such as those used in the petascale Roadrunner system. Our implementation incurs less than 3.2 mus of overhead per profile call while efficiently utilizing the limited local store of the Cell's SPE cores. We demonstrate the use of our profiler on a cluster of hybrid nodes running a suite of scientific applications. Our analyses of inter-SPE communication (across the entire cluster) and function call patterns provide valuable information that can be used to optimize application performance.