Out-of-Core Graph Coloring Algorithm

Abstract

Out-of-core algorithms can process data sets that are too large to fit entirely into the computer’s main memory. This thesis develops an out-of-core algorithm for graph coloring. It dynamically partitions the graph into subgraphs, processes them in sequence, and records the color information needed by later subgraphs in a dense format. The algorithm is guaranteed to produce the same coloring as the first-fit in-core algorithm. It employs a new method to compactly record information and automatically resizes the associated data structure to save memory. As there are no pre-existing out-of-core graph coloring codes, the implementation can only be compared to leading in-core graph coloring codes. Based on the geometric mean over 18 graphs from various domains, JP-D1 is 25% faster and uses 13% fewer colors. FirstFit and Boost both use the same number of colors as the presented implementation, but FirstFit is 4 times faster whereas Boost is 6 times slower.