In: IEEE Data Engineering Bulletin, 2020, vol. 43, no. 1, p. 60-71
Many large computer clusters offer alternative computing elements in addition to general-purpose CPUs. GPU and FPGAs are very common choices. Two emerging technologies can further widen the options in that context: in-network computing (INC) and near-storage processing (NSP). These technologies support computing over data that is in transit between nodes or inside the storage stack,...
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In: Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018, p. 437–446
The graph embedding paradigm projects nodes of a graph into a vector space, which can facilitate various downstream graph analysis tasks such as node classification and clustering. To efficiently learn node embeddings from a graph, graph embedding techniques usually preserve the proximity between node pairs sampled from the graph using random walks. In the context of a heterogeneous graph,...
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