  Effective static analyses have been proposed which infer bounds on the number
of resolutions or reductions. These have the advantage of being independent
from the platform on which the programs are executed and have been shown to be
useful in a number of applications, such as granularity control in parallel
execution. On the other hand, in distributed computation scenarios where
platforms with different capabilities come into play, it is necessary to
express costs in metrics that include the characteristics of the platform. In
particular, it is specially interesting to be able to infer upper and lower
bounds on actual execution times. With this objective in mind, we propose an
approach which combines compile-time analysis for cost bounds with a one-time
profiling of the platform in order to determine the values of certain
parameters for a given platform. These parameters calibrate a cost model which,
from then on, is able to compute statically time bound functions for procedures
and to predict with a significant degree of accuracy the execution times of
such procedures in the given platform. The approach has been implemented and
integrated in the CiaoPP system.
