Graph algorithms are becoming increasingly important for solving many problems in scientific computing, data mining and other domains. As these problems grow in scale, parallel computing resources are required to meet their computational and memory requirements. Unfortunately, the algorithms, software, and hardware that have worked well for developing mainstream parallel scientific applications are not necessarily effective for large-scale graph problems. In this paper we present the inter-relationships between graph problems, software, and parallel hardware in the current state of the art and discuss how those issues present inherent challenges in solving large-scale graph problems. The range of these challenges suggests a research agenda for the development of scalable high-performance software for graph problems.

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Multi-core spanning forest algorithms using the disjoint-set data structure Md. Mostofa Ali Patwary * Peder Refsnes* * Fredrik Manne** Abstract—We present new multi-core algorithms for computing spanning forests and connected components of large sparse graphs. The algorithms are based on the use of the disjoint-set data structure. When compared with the previous best algorithms for these problems our algorithms are appealing for several reasons: Extensive experiments using up to 40 threads on several different types of graphs show that they scale better. Also, the new algorithms do not make use of any hardware specific routines, and thus are highly portable. Finally, the algorithms are quite simple and easy to implement. Keywords-Multi-core, spanning forrest, connected components, Disjoint sets I.