Graph Partitioning Models for Parallel Computing


Calculations can naturally be described as graphs in which vertices represent computation and edges reflect 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.

Parallel Computing
B. Hendrickson, T. G. Kolda. Graph Partitioning Models for Parallel Computing. Parallel Computing, Vol. 26, No. 12, pp. 1519-1534, 2000.


Graph partitioning; hypergraph partitioning; parallel computing


author = {Bruce Hendrickson and Tamara G. Kolda}, 
title = {Graph Partitioning Models for Parallel Computing}, 
journal = {Parallel Computing}, 
volume = {26}, 
number = {12}, 
pages = {1519--1534}, 
month = {November}, 
year = {2000},
doi = {10.1016/S0167-8191(00)00048-X},