  Machine-specific optimizations command the machine to behave in a specific
way. As current programming models largely leave machine details unexposed,
they cannot accommodate direct encoding of such commands. In previous work we
have proposed the design of performance-transparent programming models to
facilitate this use-case; this report contains proof-of-concept examples of
such programming models. We demonstrate how programming model abstractions may
reveal the memory footprint, vector unit utilization and data reuse of an
application, with prediction accuracy ranging from 0 to 25 \%.
