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Parallel graph algorithm design is a very well studied topic.
Parallel Graph Connectivity in Log Diameter Rounds (with Zhao Song, Clifford Stein, Zhengyu Wang, Peilin Zhong).
Previous investigations have developed Knowledge Discovery Toolbox (KDT), a sophisticated Python library for parallel graph computations.
The Combinatorial BLAS (CombBLAS) is an extensible distributed-memory parallel graph library offering a small but powerful set of linear algebra primitives specifically targeting graph analytics.
Moreover, an extensive discussion focused on different implementation paths on GPUs shows the way to deal with parallel graph connected components.
To explore the huge design space, genetic algorithm are used on a 4 variables application case and the results are presented through a parallel graph.
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In this paper we report on our efforts to reproduce results presented in a paper titled "A Parallel Connectivity Algorithm for de Bruijn Graphs in Metagenomic Applications," which shows that the parallel graph-based algorithm developed scales to over a thousand cores, and runs faster than traditional Breadth First Search algorithms.
(2) Single source multiple sinks FCG's and GCG's on series parallel graphs.
(3) Multi source and sink FCG's on extension parallel graphs.
Sequential Parallel Graph-based Clock cycles 5 1 1 Memory Req.
That is, specifically, we use a very fast, series-parallel graph reasoner to speed up general point-based reasoning.
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