Dynamic clique counting on gpu
WebWhile there has been work on related problems such as finding maximal cliques and generalized sub-graph matching on GPUs, k-clique counting in particular has yet to be explored in depth. In this paper, we present the first parallel GPU solution specialized for the k-clique counting problem. WebApr 27, 2024 · Clique Counting Consider an undirected simple graph G(V,E) where V is the set of vertices in the graph, E is the set of edges in the graph, and Adj(v) is the adjacency list of a vertex v∈V . A k -clique in G is a complete sub-graph of G with exactly k …
Dynamic clique counting on gpu
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WebK-clique counting is a fundamental problem in network analysis which has attracted much attention in recent years. Computing the count of k-cliques in a graph for a large k (e.g., … WebJun 9, 2024 · Unfortunately, no work enables efficient butterfly counting on GPU currently. To fill this gap, we propose a GPU-based butterfly counting, called G-BFC. G-BFC addresses three main technical ...
WebII The algorithm presented is one of very few maximum clique solvers that runs on GPUs, makes use of recursion on the GPU, and supports systems with multiple GPUs. The rest of the paper is structure as follows: Section II covers background information necessary to better understand the proposed algorithm and summa- rizes related maximum clique ... WebJun 28, 2024 · We implement exact triangle counting in graphs on the GPU using three different methodologies: subgraph matching to a triangle pattern; programmable graph analytics, with a set-intersection ...
WebApr 27, 2024 · Counting k-cliques is typically done by traversing search trees starting at each vertex in the graph. An important optimization is to eliminate search tree branches … Webascalable GPU-based triangle countingsystem that consists of three major techniques. First, we design a binary search based algorithm that can increase both the thread parallelism …
WebTo address its scalability issue due to the recursive embedding of neighboring features, graph topology sampling has been proposed to reduce the memory and computational cost of training GCNs, and...
WebNov 16, 2024 · Third, we further develop a dynamic workload management technique to balance the workload across GPUs. our evaluation demonstrates that TriCore on a single GPU can count the triangles in the billion-edge Twitter graph within 24 seconds, that is, 22× faster than the state-of-the-art CPU project which uses CPUs that are 8× more expensive. flowkey price ukWebJun 27, 2014 · These GPU implementations of k-clique counting for both the graph orientation and pivoting approaches explore both vertex-centric and edge-centric parallelization schemes, and replace recursive search tree traversal with iterative traversal based on an explicitly-managed shared stack. 2 Highly Influenced View 8 excerpts, cites … greenception gc4WebParameters edgeSample and colorSample allow to apply sampling strategies that return an approximation of the actual number of cliques. The input to this command should be the … greenception cluster ledWebfor the k-clique counting problem, which are dynamic algo-rithms where the updates are batches of edge insertions and deletions. We study this problem in the parallel setting, … flowkey premium priceWebSep 1, 2024 · Triangle Counting. Many works perform triangle counting on the CPU [2,30,36,49] or the GPU [5,26,27,33,44,50, 52, 67,70]. A triangle is a 3-clique which is a special case of a -clique.... flowkey premium reviewWebApr 27, 2024 · Counting k-cliques in a graph is an important problem in graph analysis with many applications. Counting k-cliques is typically done by traversing search trees … greenception gc16WebDec 14, 2024 · Dynamic page offlining marks the page containing the faulty memory as unusable. This ensures that new allocations do not land on the page that contains the faulty memory. Unaffected applications will continue to run and additional workloads can be launched on this GPU without requiring a GPU reset. greenception 33w