Today's top high performance computing systems run applications with hundreds of thousands of processes, contain hundreds of storage nodes, and must meet massive I/O requirements for capacity and performance. These leadership-class systems face daunting challenges to deploying scalable I/O systems. In this paper we present a case study of the I/O challenges to performance and scalability on Intrepid, the IBM Blue Gene/P system at the Argonne Leadership Computing Facility. Listed in the top 5 fastest supercomputers of 2008, Intrepid runs computational science applications with intensive demands on the I/O system. We show that Intrepid's file and storage system sustain high performance under varying workloads as the applications scale with the number of processes.