Control-Flow Profiling for Workload Representativeness

arXiv:2611.16889v1 Announce Type: cross Abstract: Workload characterization in performance engineering often replaces expensive target executions with lower-cost proxies, including reduced datasets, miniapps, and training inputs. Such substitutions require empirical verification that the proxy faithfully exercises the target's dynamic execution behavior. This paper presents an address-keyed control-flow profiling methodology and tool suite designed to evaluate workload representativeness directly from compiled, unmodified binaries.