Graph partitioning models for parallel computing

Calculations can naturally be described as graphs in which vertices represent computation and edges reeect data dependencies. By partitioning the vertices of a graph, the calculation can be divided among processors of a parallel computer. However, the standard methodology for graph partitioning minimizes the wrong metric and lacks expressibility. We survey several recently proposed alternatives and discuss their relative merits.