Automatic source code specialization for energy reduction

This paper presents a framework to reduce the computational effort of software programs, using value profiling and partial evaluation. Our tool reduces computational effort by specializing a program for highly expected situations and such a reduction translates into both energy and performance improvement. Procedure calls executed frequently with same parameter values are defined as highly expected situations (common cases). The choice of the best transformation of common cases is achieved by solving three search problems. The first identifies effective common cases to be specialized, the second searches for an optimal solution for effective common case, and the third examines the interplay among the specialized cases. Our technique improves both energy consumption and performance of the source code up to more than twice and in average about 25% over the original program. Also, our pruning techniques reduce the searching time by 80% compared to exhaustive approach.