  Sparse triangular solve (SpTRSV) is an extensively studied computational
kernel. An important obstacle in parallel SpTRSV implementations is that in
some parts of a sparse matrix the computation is serial. By transforming the
dependency graph, it is possible to increase the parallelism of the parts that
lack it. In this work, we present an approach to increase the parallelism
degree of a sparse matrix, discuss its limitations and possible improvements,
and we compare it to a previous manual approach. The results provide several
hints on how to craft a collection of strategies to transform a dependency
graph.
