Goal-Directed Value Profiling
Department of Computer Science
University of Arizona
Tucson, AZ 85721, U.S.A.
Compilers can exploit knowledge that a variable has a fixed known value at a program point for optimizations such as code specialization and constant folding. Recent work has shown that it is possible to take advantage of such optimizations, and thereby obtain significant performance improvements, even if a variable cannot be statically guaranteed to have a fixed constant value. To do this profitably, however, it is necessary to take into account information about the runtime distribution of values taken on by variables. This information can be obtained though value profiling. Unfortunately, existing approaches to value profiling incur high overheads, primarily because profiling is carried out without consideration for the way in which the resulting information will be used. In this paper, we describe an approach to reduce the cost of value profiling by making the value profiler aware of the utility of the value profiles being gathered. This allows our profiler to avoid wasting resources where the profile can be guaranteed to not be useful for optimization. This results in significant reductions in both the time and space requirements for value profiling. Our approach, implemented in the context of the alto link-time optimizer, is an order of magnitude faster, and uses about 5% of the space, of a straightforward implementation.