NeuGraph: Parallel Deep Neural Network Computation on Large Graphs
暂无分享,去创建一个
Yafei Dai | Ming Wu | Jilong Xue | Lingxiao Ma | Youshan Miao | Lidong Zhou | Zhi Yang | Lidong Zhou | Ming Wu | Yafei Dai | Jilong Xue | Youshan Miao | Zhi Yang | Lingxiao Ma
[1] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[2] Rob Fergus,et al. Learning Multiagent Communication with Backpropagation , 2016, NIPS.
[3] Nanyun Peng,et al. Cross-Sentence N-ary Relation Extraction with Graph LSTMs , 2017, TACL.
[4] Razvan Pascanu,et al. Relational inductive biases, deep learning, and graph networks , 2018, ArXiv.
[5] Haibo Chen,et al. Fast and Concurrent RDF Queries using RDMA-assisted GPU Graph Exploration , 2018, USENIX Annual Technical Conference.
[6] Philip S. Yu,et al. A Comprehensive Survey on Graph Neural Networks , 2019, IEEE Transactions on Neural Networks and Learning Systems.
[7] Carlos Guestrin,et al. Distributed GraphLab : A Framework for Machine Learning and Data Mining in the Cloud , 2012 .
[8] Lise Getoor,et al. Collective Classification in Network Data , 2008, AI Mag..
[9] Jure Leskovec,et al. Inductive Representation Learning on Large Graphs , 2017, NIPS.
[10] Xavier Bresson,et al. Residual Gated Graph ConvNets , 2017, ArXiv.
[11] Max Welling,et al. Graph Convolutional Matrix Completion , 2017, ArXiv.
[12] Hao Ma,et al. GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs , 2018, UAI.
[13] Zheng Zhang,et al. MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems , 2015, ArXiv.
[14] Karsten Schwan,et al. GraphReduce: processing large-scale graphs on accelerator-based systems , 2015, SC15: International Conference for High Performance Computing, Networking, Storage and Analysis.
[15] Cao Xiao,et al. FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling , 2018, ICLR.
[16] Reynold Xin,et al. GraphX: Graph Processing in a Distributed Dataflow Framework , 2014, OSDI.
[17] Alexander S. Szalay,et al. FlashGraph: Processing Billion-Node Graphs on an Array of Commodity SSDs , 2014, FAST.
[18] Vipin Kumar,et al. A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs , 1998, SIAM J. Sci. Comput..
[19] Willy Zwaenepoel,et al. Chaos: scale-out graph processing from secondary storage , 2015, SOSP.
[20] Joan Bruna,et al. Deep Convolutional Networks on Graph-Structured Data , 2015, ArXiv.
[21] Samuel S. Schoenholz,et al. Neural Message Passing for Quantum Chemistry , 2017, ICML.
[22] Wencong Xiao,et al. GraM: scaling graph computation to the trillions , 2015, SoCC.
[23] Jure Leskovec,et al. Graph Convolutional Neural Networks for Web-Scale Recommender Systems , 2018, KDD.
[24] Xavier Bresson,et al. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering , 2016, NIPS.
[25] Richard S. Zemel,et al. Gated Graph Sequence Neural Networks , 2015, ICLR.
[26] Thang D. Bui,et al. Neural Graph Learning: Training Neural Networks Using Graphs , 2018, WSDM.
[27] Huan Liu,et al. Relational learning via latent social dimensions , 2009, KDD.
[28] Binyu Zang,et al. Bipartite-oriented distributed graph partitioning for big learning , 2014, APSys.
[29] Anton van den Hengel,et al. Image-Based Recommendations on Styles and Substitutes , 2015, SIGIR.
[30] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[31] Yafei Dai,et al. Garaph: Efficient GPU-accelerated Graph Processing on a Single Machine with Balanced Replication , 2017, USENIX Annual Technical Conference.
[32] Ming Wu,et al. Managing Large Graphs on Multi-Cores with Graph Awareness , 2012, USENIX Annual Technical Conference.
[33] Wenwu Zhu,et al. Deep Learning on Graphs: A Survey , 2018, IEEE Transactions on Knowledge and Data Engineering.
[34] Jacob Nelson,et al. Latency-Tolerant Software Distributed Shared Memory , 2015, USENIX Annual Technical Conference.
[35] F. Scarselli,et al. A new model for learning in graph domains , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..
[36] Aart J. C. Bik,et al. Pregel: a system for large-scale graph processing , 2010, SIGMOD Conference.
[37] Joseph Gonzalez,et al. PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs , 2012, OSDI.
[38] Willy Zwaenepoel,et al. X-Stream: edge-centric graph processing using streaming partitions , 2013, SOSP.
[39] Binyu Zang,et al. PowerLyra: Differentiated Graph Computation and Partitioning on Skewed Graphs , 2019, TOPC.
[40] Pietro Liò,et al. Graph Attention Networks , 2017, ICLR.
[41] Jinwook Kim,et al. GTS: A Fast and Scalable Graph Processing Method based on Streaming Topology to GPUs , 2016, SIGMOD Conference.
[42] Alexander Aiken,et al. A Distributed Multi-GPU System for Fast Graph Processing , 2017, Proc. VLDB Endow..
[43] Ah Chung Tsoi,et al. The Graph Neural Network Model , 2009, IEEE Transactions on Neural Networks.
[44] E. Xing,et al. Cavs: An Efficient Runtime System for Dynamic Neural Networks , 2018, USENIX Annual Technical Conference.
[45] Wei Li,et al. Tux2: Distributed Graph Computation for Machine Learning , 2017, NSDI.
[46] Diego Marcheggiani,et al. Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling , 2017, EMNLP.
[47] Haibo Chen,et al. Fast and Concurrent RDF Queries with RDMA-Based Distributed Graph Exploration , 2016, OSDI.
[48] Zhiyuan Liu,et al. Graph Neural Networks: A Review of Methods and Applications , 2018, AI Open.
[49] Guy E. Blelloch,et al. GraphChi: Large-Scale Graph Computation on Just a PC , 2012, OSDI.
[50] Geoffrey Zweig,et al. An introduction to computational networks and the computational network toolkit (invited talk) , 2014, INTERSPEECH.