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Automatic I/O Scheduler Selection through Online Workload Analysis

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3 Author(s)
Ramon Nou ; Barcelona Supercomput. Center, Barcelona, Spain ; Jacobo Giralt ; Toni Cortes

I/O performance is a bottleneck for many workloads. The I/O scheduler plays an important role in it. It is typically configured once by the administrator and there is no selection that suits the system at every time. Every I/O scheduler has a different behavior depending on the workload and the device. We present a method to select automatically the most suitable I/O scheduler for the ongoing workload. This selection is done online, using a workload analysis method with small I/O traces, finding common I/O patterns. Our dynamic mechanism adapts automatically to one of the best schedulers, sometimes achieving improvements on I/O performance for heterogeneous workloads beyond those of any fixed configuration (up to 5%). This technique works with any application and device type (RAID, HDD, SSD), as long as we have a system parameter to tune. It does not need disk simulations or hardware models, which are normally unavailable. We evaluate it in different setups, and with different benchmarks.

Published in:

Ubiquitous Intelligence & Computing and 9th International Conference on Autonomic & Trusted Computing (UIC/ATC), 2012 9th International Conference on

Date of Conference:

4-7 Sept. 2012