Evaluating the performance of a computer system is based on using representative workloads. Common practice is to either use real workload traces to drive simulations, or else to use statistical workload models that are based on such traces. Such models allow various workload attributes to be manipulated, thus providing desirable flexibility, but may lose details of the workload's internal structure. To overcome this, we suggest to combine the benefits of real traces and flexible modeling. Focusing on the problem of evaluating the performance of parallel job schedulers, we partition each trace into independent subtraces representing different users, and then re-combine them in various ways, while maintaining features like the daily and weekly cycles of activity. This facilitates the creation of longer workload traces that enable longer simulations, the creation of multiple statistically similar workloads that can be used to gauge confidence intervals, and the creation of workloads with different load levels.