Scalable Graph Embedding LearningOn A Single GPU. (arXiv:2110.06991v2 [cs.LG] UPDATED)

Graph embedding techniques have attracted growing interest since they convert
the graph data into continuous and low-dimensional space. Effective graph
analytic provides users a deeper understanding of what is behind the data and
thus can benefit a variety of machine learning tasks. With the current scale of
real-world applications, most graph analytic methods suffer high computation
and space costs. These methods and systems can process a network with thousands
to a few million nodes. However, scaling to large-scale networks remains …

arxiv embedding gpu graph