Browsing by Author "Gagie, Travis"
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Item Fast and Compact Planar Embeddings(2017) Ferres, Leo; Fuentes-Sepúlveda, José; Gagie, Travis; He, MengThere are many representations of planar graphs, but few are as elegant as Turan's (1984): it is simple and practical, uses only 4 bits per edge, can handle self-loops and multiedges, and can store any specified embedding. Its main disadvantage has been that "it does not allow efficient searching" (Jacobson, 1989). In this paper we show how to add a sublinear number of bits to Turan's representation such that it supports fast navigation while retaining simplicity. As a consequence of the inherited simplicity, we offer the first efficient parallel construction of a compact encoding of a planar graph embedding. Our experimental results show that the resulting representation uses about 6 bits per edge in practice, supports basic navigation operations within a few microseconds, and can be built sequentially at a rate below 1 microsecond per edge, featuring a linear speedup with a parallel efficiency around 50% for large datasets. (C) 2020 Elsevier B.V. All rights reservedItem Fast and compact planar embeddings(2020) Ferres, Leo; Fuentes-Sepúlveda, José; Gagie, Travis; He, Meng; Navarro, GonzaloThere are many representations of planar graphs, but few are as elegant as Turán’s (1984): it is simple and practical, uses only 4 bits per edge, can handle self-loops and multiedges, and can store any specified embedding. Its main disadvantage has been that “it does not allow efficient searching” (Jacobson, 1989). In this paper we show how to add a sublinear number of bits to Turán’s representation such that it supports fast navigation while retaining simplicity. As a consequence of the inherited simplicity, we offer the first efficient parallel construction of a compact encoding of a planar graph embedding. Our experimental results show that the resulting representation uses about 6 bits per edge in practice, supports basic navigation operations within a few microseconds, and can be built sequentially at a rate below 1 microsecond per edge, featuring a linear speedup with a parallel efficiency around 50% for large datasets.Item Fast and Compact Planar Embeddings(2019) Ferres, Leo; Fuentes-Sepúlveda, José; Gagie, Travis; He, Meng; Navarro, GonzaloThere are many representations of planar graphs, but few are as elegant as Turán’s (1984): it is simple and practical, uses only 4 bits per edge, can handle self-loops and multi-edges, and can store any specified embedding. Its main disadvantage has been that “it does not allow efficient searching” (Jacobson, 1989). In this paper we show how to add a sublinear number of bits to Turán’s representation such that it supports fast navigation while retaining simplicity. As a consequence of the inherited simplicity, we offer the first efficient parallel construction of a compact encoding of a planar graph embedding. Our experimental results show that the resulting representation uses about 6 bits per edge in practice, supports basic navigation operations within a few microseconds, and can be built sequentially at a rate below 1 microsecond per edge, featuring a linear speedup with a parallel efficiency around 50% for large datasets.