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Computational science applications are driving a demand for increasingly powerful storage systems. While many techniques are available for capturing the I/O behavior of individual application trial runs and specific components of the storage system, continuous characterization of a production system remains a daunting challenge for systems with hundreds of thousands of compute cores and multiple petabytes of storage. As a result, these storage systems are often designed without a clear understanding of the diverse computational science workloads they will support. In this paper, the authors outline a methodology for scalable, continuous, system-wide I/O characterization that combines storage device instrumentation, static file system analysis, and a new mechanism for capturing detailed application-level behavior.
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