A Novel Multithreaded Algorithm for Extracting Maximal Chordal Subgraphs

Chordal graphs are triangulated graphs where any cycle larger than three is bisected by a chord. Many combinatorial optimization problems such as computing the size of the maximum clique and the chromatic number are NP-hard on general graphs but have polynomial time solutions on chordal graphs. In this paper, we present a novel multithreaded algorithm to extract a maximal chordal sub graph from a general graph. We develop an iterative approach where each thread can asynchronously update a subset of edges that are dynamically assigned to it per iteration and implement our algorithm on two different multithreaded architectures - Cray XMT, a massively multithreaded platform, and AMD Magny-Cours, a shared memory multicore platform. In addition to the proof of correctness, we present the performance of our algorithm using a test set of synthetical graphs with up to half-a-billion edges and real world networks from gene correlation studies and demonstrate that our algorithm achieves high scalability for all inputs on both types of architectures

Parallel Shortest Path Algorithms for Solving Large-Scale Instances

We present an experimental study of parallel algorithms for solving the single source shortest path problem with non-negative edge weights (NSSP) on large-scale graphs. We implement Meyer and Sander's Δ-stepping algorithm and report performance results on the Cray MTA-2, a multithreaded parallel architecture. The MTA-2 is a high-end shared memory system offering two unique features that aid the efficient implementation of irregular parallel graph algorithms: the ability to exploit fine-grained parallelism, and low-overhead synchronization primitives. Our implementation exhibits remarkable parallel speedup when compared with a competitive sequential algorithm, for low-diameter sparse graphs. For instance, Δ-stepping on a directed scale-free graph of 100 million vertices and 1 billion edges takes less than ten seconds on 40 processors of the MTA-2, with a relative speedup of close to 30. To our knowledge, these are the first performance results of a parallel NSSP problem on realistic graph instances in the order of billions of vertices and edges