Workload synthesis: Generating benchmark workloads from statistical execution profile
Keun‐Soo Kim, Changmin Lee, Jung Ho Jung, Won Woo Ro · 2014
We propose an approach for benchmark workload generation. The proposed workload synthesis generates synthetic workloads that model the behavior of real applications. Statistical execution profile of a workload is constructed from hardware performance counters available in recent processors, and the overhead of profiling is significantly lower than instrumentation or simulation which requires inspection of instruction stream. Workload synthesis can be applied even though the source codes or binaries of real applications are not available, because it utilizes only statistical profile. In addition, for non-deterministic workloads, using synthetic workloads provides more consistent results than executing real workloads, since a synthetic workload replays predetermined instructions reconstructed from the execution profile of a real workload. Furthermore, with a sampling technique, we can reduce the execution time of synthetic workloads while preserving its run-time characteristics. We have implemented and evaluated the proposed method on ARM-based mobile devices. The results show that synthetic workloads reproduce the profiled performance event counts of real workloads with high accuracy.