  A workload analysis technique is presented that processes data from operation
type traces and creates a Hidden Markov Model (HMM) to represent the workload
that generated those traces. The HMM can be used to create representative
traces for performance models, such as simulators, avoiding the need to
repeatedly acquire suitable traces. It can also be used to estimate directly
the transition probabilities and rates of a Markov modulated arrival process,
for use as input to an analytical performance model of Flash memory. The HMMs
obtained from industrial workloads are validated by comparing their
autocorrelation functions and other statistics with those of the corresponding
monitored time series. Further, the performance model applications are
illustrated by numerical examples.
