A new approach to I/O performance evaluation

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Abstract
Current I/O benchmarks suffer from several chronic problems: they quickly become obsolete; they do not stress the I/O system; and they do not help much in understanding I/O system performance. We propose a new approach to I/O performance analysis. First, we propose a self-scaling benchmark that dynamically adjusts aspects of its workload according to the performance characteristic of the system being measured. By doing so, the benchmark automatically scales across current and future systems. The evaluation aids in understanding system performance by reporting how performance varies according to each of five workload parameters. Second, we propose predicted performance, a technique for using the results from the self-scaling evaluation to estimate quickly the performance for workloads that have not been measured. We show that this technique yields reasonably accurate performance estimates and argue that this method gives a far more accurate comparative performance evaluation than traditional single-point benchmarks. We apply our new evaluation technique by measuring a SPARCstation 1+ with one SCSI disk, an HP 730 with one SCSI-II disk, a DECstation 5000/200 running the Sprite LFS operating system with a three-disk disk array, a Convex C240 minisupercomputer with a four-disk disk array, and a Solbourne 5E/905 fileserver with a two-disk disk array.

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