By now, irregular problems are difficult to parallelize in an automatic way because of their lack of regularity in data access patterns. Most times, programmers must hand-write a particular solution for each problem separately. In this paper we present two pseudo-regular distributions which can be applied to partition most problems achieving very good average case distributions. Also, we have designed a run-time library (DDLY) which provides a fast way to apply data distribution on message passing environments. This library also is able of performing parallel input/output.