Parallel skeletons and homomorphisms over lists provide successful methods for parallelization. Several implementations exist due to their simplicity, which casts a contrast to more complicated data structures like trees. With assigning additional information properly, we know data structures can be coded into a list.

This paper develops a unified approach toward nested parallelism where data structures are represented into lists of tuples with depth information. Generic parallel computation schemes like reduce and accumulations are defined using the idea of list homomorphism. We demonstrate its uniformity and expressiveness using examples.