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- W2903539791 abstract "List intersections are ubiquitous and can be found in a wide range of applications, including triangle counting and finding the maximal k-truss, both of which are part of the HPEC Static Graph Challenge. For many graph based problems it is necessary to find intersections for a very large number of lists–these lists tend to vary greatly in size and are difficult to efficiently load-balance. Numerous parallel algorithms on list intersections for triangle counting have been proposed, but load-balancing decisions are typically made at a global level. In this paper we present an efficient and adaptive approach to load-balancing at a finer granularity. Our approach assigns a different number of threads for different intersections in order to effectively utilize the resources of the GPU. We show the applicability of our load-balancing method to two different intersection methods, one search-based and one merge-based. Our algorithm outperforms several recent triangle counting algorithms, including recent HPEC Graph Challenge Champions." @default.
- W2903539791 created "2018-12-11" @default.
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- W2903539791 date "2018-09-01" @default.
- W2903539791 modified "2023-10-13" @default.
- W2903539791 title "Fast and Adaptive List Intersections on the GPU" @default.
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- W2903539791 doi "https://doi.org/10.1109/hpec.2018.8547759" @default.
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