Energy efficiency is of steadily growing importance in virtually all areas from mobile to high performance computing. Therefore, lots of research projects focus on this topic and strongly rely on power measurements from their test platforms. The need for finer grained measurement data-both in terms of temporal and spatial resolution (component breakdown)-often collides with very rudimentary measurement setups that rely e.g., on non-professional power meters, IMPI based platform data or model-based interfaces such as RAPL or APM. This paper presents an in-depth study of several different AC and DC measurement methodologies as well as model approaches on test systems with the latest processor generations from both Intel and AMD. We analyze most important aspects such as signal quality, time resolution, accuracy, and measurement overhead and use a calibrated, professional power analyzer as our reference.

Modern model-based development methodologies require a large number of efficient, high-quality model comparison tools. They must be carefully adapted to the specific model type, user preferences and application context. Implementing a large number of dedicated, monolithic tools is infeasible, the only viable approach are generic, adaptable tools. Generic tools currently available provide only partial or low-quality solutions to this challenge; their results are not satisfactory for model types such as state machines or block diagrams. This paper presents the SiDiff approach to model comparison which includes a set of highly configurable incremental matchers and a specification language to control their application.