| [1] 王虹旭, 吴斌, 刘旸. 基于Spark的并行图数据分析系统[J]. 计算机科学与探索,2015,9(9):1066-1074.(WANG H X,WU B, LIU Y. Parallel graph data analysis system based on Spark[J]. Journal of Frontiers of Computer Science and Technology,2015,9(9):1066-1074.) [2] HOEFLER T, SCHNEIDER T. Optimization principles for collective neighborhood communications[C]//Proceedings of the 2012 International Conference for High Performance Computing, Networking, Storage and Analysis. Piscataway:IEEE, 2012:1-10.
 [3] LU Y,CHENG J,YAN D,et al. Large-scale distributed graph computing systems:an experimental evaluation[J]. Proceedings of the VLDB Endowment,2014,8(3):281-292.
 [4] LUMSDAINE A, GREGOR D, HENDRICKSON B, et al. Challenges in parallel graph processing[J]. Parallel Processing Letters,2007,17(1):5-20.
 [5] XIE C, YAN L, LI W, et al. Distributed power-law graph computing:theoretical and empirical analysis[C]//Proceedings of the 27th International Conference on Neural Information Processing Systems. Cambridge:MIT Press,2014:1673-1681.
 [6] MALEWICZ G,AUSTERN M H,BIK A J C,et al. Pregel:a system for large-scale graph processing[C]//Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data. New York:ACM,2010:135-146.
 [7] SALIHOGLU S,WIDOM J. GPS:a graph processing system[C]//Proceedings of the 25th International Conference on Scientific and Statistical Database Management. New York:ACM,2013:No. 22.
 [8] EDMONDS N,WILLCOCK J,LUMSDAINE A. Expressing graph algorithms using generalized active messages[C]//Proceedings of the 18th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. New York:ACM,2013:289-290.
 [9] AVERY C. Giraph:large-scale graph processing infrastructure on Hadoop[J]. Proceedings of the Hadoop Summit,2011,11(3):5-9.
 [10] WILLCOCK J J,HOEFLER T,EDMONDS N G,et al. Active pebbles:parallel programming for data-driven applications[C]//Proceedings of the 2011 International Conference on Supercomputing. New York:ACM,2011:235-244.
 [11] NELSON J,HOLT B,MYERS B,et al. Latency-tolerant software distributed shared memory[C]//Proceedings of the 2015 USENIX Annual Technical Conference. Berkeley:USENIX Association, 2015:291-305.
 [12] FIDEL A,AMATO N M,RAUCHWERGER L. The STAPL parallel graph library[C]//Proceedings of the 2012 International Workshop on Languages and Compilers for Parallel Computing. Berlin:Springer,2012:46-60.
 [13] KUMAR S,SABHARWAL Y,GARG R,et al. Optimization of all-to-all communication on the Blue Gene/L supercomputer[C]//Proceedings of the 37th International Conference on Parallel Processing. Piscataway:IEEE,2008:320-329.
 [14] LIN H,ZHU X,YU B,et al. ShenTu:processing multi-trillion edge graphs on millions of cores in seconds[C]//Proceedings of the 2018 International Conference for High Performance Computing, Networking, Storage and Analysis. Piscataway:IEEE,2018:706-716.
 [15] WESOLOWSKI L, VENKATARAMAN R, GUPTA A, et al. TRAM:optimizing fine-grained communication with topological routing and aggregation of messages[C]//Proceedings of the 43rd International Conference on Parallel Processing. Piscataway:IEEE,2014:211-220.
 [16] DI STEFANO L, BULGARELLI A. A simple and efficient connected components labeling algorithm[C]//Proceedings of the 10th International Conference on Image Analysis and Processing. Piscataway:IEEE,1999:322-327.
 [17] CHAKRABARTI D, ZHAN Y, FALOUTSOS C. R-MAT:a recursive model for graph mining[C]//Proceedings of the 2004 SIAM International Conference on Data Mining. Philadelphia, PA:SIAM,2004:442-446.
 [18] SESHADHRI C,PINAR A,KOLDA T G. An in-depth study of stochastic Kronecker graphs[C]//Proceedings of the IEEE 11th International Conference on Data Mining. Piscataway:IEEE, 2011:587-596.
 [19] GREGOR D,LUMSDAINE A. Lifting sequential graph algorithms for distributed-memory parallel computation[J]. ACM SIGPLAN Notices,2005,40(10):423-437.
 |