Distributed graph computation is central to applications ranging from language processing to social networks. However, natural graphs tend to have skewed power-law distributions where a small subset of the vertices have a large number of neighbors. Existing graph-parallel systems suffer from load imbala...
but instead exhibit power-law distributed samples. In this paper, we propose a graph theoretic approach to matrix completion that solves the problem for more realistic sampling models. Our method is easier to analyze than previous methods with the analysis reducing to computing the threshold for...
Figure 1 depicts the performance on the PowerLaw Clus- tered graph [18] of size 1,000 with 4 partitions. This is one of our synthetic graphs where the model is intended to capture power law graphs observed in nature. The lower bound pro- vided by METIS is 58.9% of the edges cut, ...
Among them, only (1) has been studied by existing systems, but many real-world power-law graphs also exhibit the characteristics of (2) and (3). In this paper, we propose a block-centric framework, called Blogel, which naturally handles all the three adverse graph characteristics. Blogel ...
GraphLab also includes specific optimizations that allow for balanced and efficient distribution of work among nodes processing graphs that have power-law distribution, such as social and web graphs.Here's a comparison of distributed analytics engines:...
& You, F. Quantum computing for energy systems optimization: challenges and opportunities. Energy 179, 76–89 (2019). Article Google Scholar Harrigan, M. et al. Quantum Approximate Optimization of Non-Planar Graph Problems on a Planar Superconducting Processor, arXiv:2004.04197v1 (2020). ...
We estimated the betweenness centrality of the huge Twitter networks [3] and found that its distribution follows a power law. 展开 关键词: X10 betweenness centrality parallel processing PGAS DOI: 10.1109/HiPC.2013.6799143 被引量: 5 年份: 2014 ...
Hybrid Classical/Quantum algorithms:These are the classes of problems that combine both classical and quantum methodology to generate the result. As these algorithms are leveraged with computing power of both the classical and quantum systems, they provide higher efficiency and better speed. Some exampl...
This approach is composed of two parts: one that learns the static properties of the graph and a dynamic aspect that models the dependencies of the temporal dynamics of the TDGs as a function of time. Anomalous traffic is defined as the traffic caused by different forms of illegal computing ...
graph and are more meaningful for assessing the state of the whole network and comparing different structures. In contrast, local metrics are calculated on each node’s immediate neighbourhood and provide more detailed insight while requiring fewer computing resources50. Spectral metrics refer to the ...