Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable

Scalable parallel graph coloring algorithms

Finding a good graph coloring quickly is often a crucial phase in the development of efficient, parallel algorithms for many scientific and engineering applications. In this paper we consider the problem of solving the graph coloring problem itself in parallel. We present a simple and fast parallel graph coloring heuristic that is well suited for shared memory programming and yields an almost l...

Efficient and scalable parallel graph partitioning

The realization of efficient parallel graph partitioners requires the parallelization of the multi-level framework which is commonly used to improve the quality and speed of sequential partitioners. The two most critical issues in this framework are the coarsening phase, and the local refinement step performed in the uncoarsening phase. These two phases are difficult to parallelize, because the...

Fast and Scalable Parallel Algorithms forMatrix

Scalable Coarse Grained Parallel Interval Graph Algorithms

We present scalable coarse grained parallel algorithms for solving interval graph problems on a BSP-like model{Coarse Grained Multicomputers (CGM). The problems we consider include: nding maximum independent set, maximum weighted clique, minimum coloring and cut vertices and bridges. With scalability at n p p ; 8 > 0 (here n denotes the total input size and p the number of processors), our algo...

Efficient Parallel Graph Algorithms in Python

Domain experts in a variety of fields utilize large-scale graph analysis; however, creating high-performance parallel graph applications currently involves expertise in both graph theory and parallel programming which might not be available to the domain specialist. This project explores methods for bringing efficient parallel performance to graph applications written in Python using selective ...