Date Added: Oct 2009
The authors engineer algorithms for sorting huge data sets on massively parallel machines. The algorithms are based on the multiway merging paradigm. They first outline an algorithm whose I/O requirement is close to a lower bound. Thus, in contrast to naive implementations of multiway merging and all other approaches known to one, the algorithm works with just two passes over the data even for the largest conceivable inputs. A second algorithm reduces communication overhead and uses more conventional specifications of the result at the cost of slightly increased I/O requirements. An implementation wins the well known sorting benchmark in several categories and by a large margin over its competitors.