Abstract

Optimizing compilers require accurate dependence testing to enable numerous, performance-enhancing transformations. However, data dependence testing is a difficult problem, particularly in the presence of pointers. Though existing approaches work well for pointers to named memory locations (i.e. other variables) , they are overly conservative in the case of pointers to unnamed memory locations. The latter occurs in the context of dynamic, pointer-based data structures, used in a variety of applications ranging from system software to computational geometry to N-body and circuit simulations. In this paper we present a new technique for performing more accurate data dependence testing in the presence of dynamic, pointer-based data structures. We will demonstrate its effectiveness by breaking false dependences that existing approaches cannot, and provide results which show that removing these dependences enables significant parallelization of a real application. 1 Introduction and Motiv...

Citations