Results 11 to 20 of about 197,409 (310)
IEEE Transactions on Quantum Engineering, 2023 It is important for the design of a distributed quantum circuit (DQC) to minimize the communication cost in k-way balanced partitioning. In this article, given an original quantum circuit (QC), a partitioning number k, the maximum capacity δ ...
Jin-Tai Yan
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IEEE Access, 2022 Skeleton-based Graph Convolutional Networks (GCN) for human action and interaction recognition have received considerable attention of researchers due to its compact and view-invariant nature of skeleton data.
Quanyu Wang +2 more
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Label Propagation-Based Parallel Graph Partitioning for Large-Scale Graph Data
IEEE Access, 2020 The increasing importance of graph data in various fields requires large-scale graph data to be processed efficiently. Furthermore, well-balanced graph partitioning is a vital component of parallel/distributed graph processing.
Minho Bae, Minjoong Jeong, Sangyoon Oh
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Graph partitioning: an updated survey
AKCE International Journal of Graphs and Combinatorics, 2023 Graph partitioning problem, which is one of the most important topics in graph theory, usually asks for a partition of the vertex set of a graph into pairwise disjoint subsets with various requirements. It comes from the well-known Max-Cut Problem: Given
Shufei Wu, Jianfeng Hou
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Deep Multilevel Graph Partitioning
29th Annual European Symposium on Algorithms (ESA 2021), 2021 Partitioning a graph into blocks of "roughly equal" weight while cutting only few edges is a fundamental problem in computer science with a wide range of applications. In particular, the problem is a building block in applications that require parallel processing. While the amount of available cores in parallel architectures has significantly increased
Gottesbüren, Lars +4 more
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Standard Framework for Comparison of Graph Partitioning Techniques
JISR on Computing, 2015 Graph Partitioning is used to distribute graph partitions across nodes for processing. It is very important in the pre-processing step for distributed graph processing.
Mudasser Iqbal, Saif-ur-Rahman
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Adaptive Partitioning for Large-Scale Dynamic Graphs [PDF]
, 2013 —In the last years, large-scale graph processing has gained increasing attention, with most recent systems placing particular emphasis on latency. One possible technique to improve runtime performance in a distributed graph processing system is to reduce
Cuadrado, F +4 more
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Buffered Streaming Graph Partitioning
ACM Journal of Experimental Algorithmics, 2022 Partitioning graphs into blocks of roughly equal size is a widely used tool when processing large graphs. Currently, there is a gap observed in the space of available partitioning algorithms. On the one hand, there are streaming algorithms that have been adopted to partition massive graph data on small machines.
Marcelo Fonseca Faraj, Christian Schulz
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GAP: Genetic Algorithm Based Large-Scale Graph Partition in Heterogeneous Cluster
IEEE Access, 2020 Graph is an important model to describe various networks, and its scale becomes larger and larger with the development of communication and information technology.
Menghan Li +3 more
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Revisiting the Isoperimetric Graph Partitioning Problem
IEEE Access, 2019 Isoperimetric graph partitioning, which is also known as the Cheeger cut, is NP-hard in its original form. In the literature, multiple modifications to this problem have been proposed to obtain approximation algorithms for clustering applications. In the
Sravan Danda +3 more
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