  We present GraSSP, a novel approach to perform automated parallelization
relying on recent advances in formal verification and synthesis. GraSSP
augments an existing sequential program with an additional functionality to
decompose data dependencies in loop iterations, to compute partial results, and
to compose them together. We show that for some classes of the sequential
prefix sum problems, such parallelization can be performed efficiently.
