Resource-Bounded Partial Evaluation
Department of Computer Science
University of Arizona
Tucson, AZ 85721, U.S.A.
Most partial evaluators do not take the availability of machine-level resources, such as registers or cache, into consideration when making their specialization decisions. The resulting resource contention can lead to severe performance degradation---causing, in extreme cases, the specialized code to run slower than the unspecialized code. In this paper we consider how resource considerations can be incorporated within a partial evaluator. We develop an abstract formulation of the problem, show that optimal resource-bounded partial evaluation is NP-complete, and discuss simple heuristics that can be used to address the problem in practice.