A Framework for Reproducible Data Plane Performance Modeling

ABSTRACTLanguages for programming data planes like P4 sparked a plethora of new applications in the data plane. The dynamic, evolving environment makes it challenging to understand what performance can be expected when running a program in a specific data plane target. However, knowing this is crucial for network operators when upgrading their networks. We present a framework for the reproducible analysis and modeling of P4 program components. By defining and generating precise specifications of the experiments, we separate fully auto-generated components from testbed- or target-specific parts. Measurement results are used to derive performance models automatically. These can then be used to compare the measured with the theoretical performance, or to model the cost of entire paths through the data plane. In two case studies, we use our framework to discover and model selected behavior for a DPDK-based software target and for the NFP-4000 SmartNIC platform.