Data-race detection: the missing piece for an end-to-end semantic equivalence checker for parallelizing transformations of array-intensive programs

Abstract

The parallelizing transformation (hand-crafted or compiler-assisted) is error prone as it is often performed without verifying any semantic equivalence with the sequential counterpart. Even when the parallel program can be proved to be semantically equivalent with its corresponding sequential program, detecting data-race conditions in the parallel program remains a challenge. In this paper, we propose a formal verification approach that can detect data-race conditions while verifying the computational semantic equivalence of parallelizing loop transformations. We propose a coloured array data dependence graph (C-ADDG) based modeling of a program for verification of program equivalence as well as data-race condition detection across parallel loops. We have tested our tool on a set of Rodinia and PLuTo+ benchmarks and shown that our method is sound, whereby the method does not produce any false-positive program equivalence or data-race condition.