Technologies (FAST ’14) is sponsored by Automatic Identification of Application I/O Signatures from Noisy Server-Side Traces

Competing workloads on a shared storage system cause I/O resource contention and application performance va-garies. This problem is already evident in today’s HPC storage systems and is likely to become acute at ex-ascale. We need more interaction between application I/O requirements and system software tools to help al-leviate the I/O bottleneck, moving towards I/O-aware job scheduling. However, this requires rich techniques to capture application I/O characteristics, which remain evasive in production systems. Traditionally, I/O characteristics have been obtained using client-side tracing tools, with drawbacks such as non-trivial instrumentation/development costs, large trace traffic, and inconsistent adoption. We presen