## Conference/Workshops

[1] L. Chen, J. Li, C. Sahinalp, M. Marathe, A. Vullikanti, A. Nikolaev, E. Smirnov, R. Israfilov, and J. Qiu, “Subgraph2vec: Highly-vectorized tree-like subgraph counting,” in 2019 IEEE International Conference on Big Data, IEEE, 2019.

[2] J. Li, F. Wang, and Q. J. Araki, Takuya, “Generalized sparse matrix-matrix multiplication for vector engines and graph applications,” in MCHPC’19: Workshop on Memory Centric High Performance Computing, ACM, 2019.

[3] C. Widanage, J. Li, S. Tyagi, R. Teja, B. Peng, S. Kamburugamuve, D. Baum, D. Smith, J. Qiu, and J. Koskey, “Anomaly detection over streaming data: Indy500 case study,” in 2019 IEEE 12th International Conference on Cloud Computing (CLOUD), pp. 9–16, IEEE, 2019.

[4] B. Peng, L. Chen, J. Li, M. Jiang, S. Akkas, E. Smirnov, R. Israfilov, S. Khekhnev, A. Nikolaev, and J. Qiu, “Harpgbdt: Optimizing gradient boosting decision tree for parallel efficiency,” in 2019 IEEE International Conference on Cluster Computing (CLUSTER), pp. 1–11, IEEE, 2019.

[5] L. Jiang, L. Chen, and J. Qiu, “Performance characterization of multi- threaded graph processing applications on many-integrated-core architec- ture,” in 2018 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), pp. 199–208, IEEE, 2018.

[6] B. Peng, B. Zhang, L. Chen, M. Avram, R. Henschel, C. Stewart, S. Zhu, E. Mccallum, L. Smith, T. Zahniser, et al., “Harplda+: Optimizing la- tent dirichlet allocation for parallel efficiency,” in 2017 IEEE International Conference on Big Data (Big Data), pp. 243–252, IEEE, 2017.

[7] L. Chen, B. Peng, B. Zhang, T. Liu, Y. Zou, L. Jiang, R. Henschel, C. Stew- art, Z. Zhang, E. Mccallum, et al., “Benchmarking harp-daal: High perfor- mance hadoop on knl clusters,” in 2017 IEEE 10th International Confer- ence on Cloud Computing (CLOUD), pp. 82–89, IEEE, 2017.

[8] B. Zhang, B. Peng, and J. Qiu, “Model-centric computation abstractions in machine learning applications,” in Proceedings of the 3rd ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond, p. 3, ACM, 2016.

[9] B. Zhang, B. Peng, and J. Qiu, “High performance lda through collective model communication optimization,” Procedia Computer Science, vol. 80, pp. 86–97, 2016.

[10] B. Zhang, Y. Ruan, and J. Qiu, “Harp: Collective communication on hadoop,” in 2015 IEEE International Conference on Cloud Engineering, pp. 228–233, IEEE, 2015.

[11] X. Gao, E. Ferrara, and J. Qiu, “Parallel clustering of high-dimensional social media data streams,” in 2015 15th IEEE/ACM International Sym- posium on Cluster, Cloud and Grid Computing, pp. 323–332, IEEE, 2015.

[12] J. Qiu, S. Jha, A. Luckow, and G. C. Fox, “Towards hpc-abds: an initial high-performance big data stack,” Building Robust Big Data Ecosystem ISO/IEC JTC, vol. 1, pp. 18–21, 2014.

[13] T.-L. Wu, A. Koppula, and J. Qiu, “Integrating pig with harp to support iterative applications with fast cache and customized communication,” in Proceedings of the 5th International Workshop on Data-Intensive Comput- ing in the Clouds, pp. 33–39, IEEE Press, 2014.

[14] S. Jha, J. Qiu, A. Luckow, P. Mantha, and G. C. Fox, “A tale of two data-intensive paradigms: Applications, abstractions, and architectures,” in 2014 IEEE International Congress on Big Data, pp. 645–652, IEEE, 2014.

[15] T. Gunarathne, J. Qiu, and D. Gannon, “Towards a collective layer in the big data stack,” in 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 236–245, IEEE, 2014.

[16] X. Gao and J. Qiu, “Supporting queries and analyses of large-scale social media data with customizable and scalable indexing techniques over nosql databases,” in 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 587–590, IEEE, 2014.

[17] G. C. Fox, S. Jha, J. Qiu, and A. Luckow, “Towards an understanding of facets and exemplars of big data applications,” in Proceedings of the 20 Years of Beowulf Workshop on Honor of Thomas Sterling’s 65th Birthday, pp. 7–16, ACM, 2014.

[18] X. Gao and J. Qiu, “Supporting end-to-end social media data analysis with the indexedhbase platform,” in Proceedings of the 6th workshop on many- task computing on clouds, grids, and supercomputers (MTAGS) at SC13, Citeseer, 2013.

[19] B. Zhang and J. Qiu, “High performance clustering of social images in a map-collective programming model,” in Proceedings of the 4th annual Symposium on Cloud Computing, p. 44, ACM, 2013.

[20] S. E. Abdelhamid, R. Alo, S. Arifuzzaman, P. Beckman, M. H. Bhuiyan, K. Bisset, E. A. Fox, G. C. Fox, K. Hall, S. S. Hasan, J. Qiu, et al., “Cinet: A cyberinfrastructure for network science,” in 2012 IEEE 8th International Conference on E-Science, pp. 1–8, IEEE, 2012.

[21] L. Stanberry, R. Higdon, W. Haynes, N. Kolker, W. Broomall, S. Ekanayake, A. Hughes, Y. Ruan, J. Qiu, E. Kolker, et al., “Visualiz- ing the protein sequence universe,” in Proceedings of the 3rd international workshop on Emerging computational methods for the life sciences, pp. 13– 22, ACM, 2012.

[22] A. Hughes, Y. Ruan, S. Ekanayake, S.-H. Bae, Q. Dong, M. Rho, J. Qiu, and G. Fox, “Interpolative multidimensional scaling techniques for the iden- tification of clusters in very large sequence sets,” in BMC bioinformatics, vol. 13, p. S9, BioMed Central, 2012.

[23] Y. Ruan, Z. Guo, Y. Zhou, J. Qiu, and G. Fox, “Hymr: a hybrid mapre- duce workflow system,” in Proceedings of the 3rd international workshop on Emerging computational methods for the life sciences, pp. 39–48, ACM, 2012.

[24] J. Y. Choi, H. Abbasi, D. Pugmire, N. Podhorszki, S. Klasky, C. Capdevila, M. Parashar, M. Wolf, J. Qiu, and G. Fox, “Mining hidden mixture context with adios-p to improve predictive pre-fetcher accuracy,” in 2012 IEEE 8th International Conference on E-Science, pp. 1–8, IEEE, 2012.

[25] S.-H. Bae, J. Qiu, and G. Fox, “Adaptive interpolation of multidimensional scaling,” Procedia Computer Science, vol. 9, pp. 393–402, 2012.

[26] H. Li, G. Fox, and J. Qiu, “Performance model for parallel matrix multipli- cation with dryad: Dataflow graph runtime,” in 2012 Second International Conference on Cloud and Green Computing, pp. 675–683, IEEE, 2012.

[27] Y. Ruan, S. Ekanayake, M. Rho, H. Tang, S.-H. Bae, J. Qiu, and G. Fox, “Dacidr: deterministic annealed clustering with interpolative dimension reduction using a large collection of 16s rrna sequences,” in Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine, pp. 329–336, ACM, 2012.

[28] T. Gunarathne, B. Zhang, T.-L. Wu, and J. Qiu, “Portable parallel pro- gramming on cloud and hpc: Scientific applications of twister4azure,” in 2011 Fourth IEEE International Conference on Utility and Cloud Comput- ing, pp. 97–104, IEEE, 2011.

[29] H. Li, Y. Ruan, Y. Zhou, J. Qiu, and G. Fox, “Design patterns for scientific applications in dryadlinq ctp,” in Proceedings of the second international workshop on Data intensive computing in the clouds, pp. 61–70, ACM, 2011.

[30] A. J. Younge, R. Henschel, J. T. Brown, G. Von Laszewski, J. Qiu, and G. C. Fox, “Analysis of virtualization technologies for high performance computing environments,” in 2011 IEEE 4th International Conference on Cloud Computing, pp. 9–16, IEEE, 2011.

[31] Y. Luo, Z. Guo, Y. Sun, B. Plale, J. Qiu, and W. W. Li, “A hierarchical framework for cross-domain mapreduce execution,” in Proceedings of the second international workshop on Emerging computational methods for the life sciences, pp. 15–22, ACM, 2011.

[32] T. Gunarathne, T.-L. Wu, J. Y. Choi, S.-H. Bae, and J. Qiu, “Cloud com- puting paradigms for pleasingly parallel biomedical applications,” Concur- rency and Computation: Practice and Experience, vol. 23, no. 17, pp. 2338– 2354, 2011.

[33] J. Y. Choi, S.-H. Bae, J. Qiu, B. Chen, and D. Wild, “Browsing large- scale cheminformatics data with dimension reduction,” Concurrency and Computation: Practice and Experience, vol. 23, no. 17, pp. 2315–2325, 2011.

[34] J. Ekanayake, H. Li, B. Zhang, T. Gunarathne, S.-H. Bae, J. Qiu, and G. Fox, “Twister: a runtime for iterative mapreduce,” in Proceedings of the 19th ACM international symposium on high performance distributed computing, pp. 810–818, ACM, 2010.

[35] J. Qiu, S. Beason, S.-H. Bae, S. Ekanayake, and G. Fox, “Performance of windows multicore systems on threading and mpi,” in 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Com- puting, pp. 814–819, IEEE, 2010.

[36] J. Y. Choi, S.-H. Bae, X. Qiu, and G. Fox, “High performance dimen- sion reduction and visualization for large high-dimensional data analysis,” in Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp. 331–340, IEEE Computer Society, 2010.

[37] J. Y. Choi, J. Qiu, M. Pierce, and G. Fox, “Generative topographic map- ping by deterministic annealing,” Procedia Computer Science, vol. 1, no. 1, pp. 47–56, 2010.

[38] S.-H. Bae, J. Qiu, and G. C. Fox, “Multidimensional scaling by determin- istic annealing with iterative majorization algorithm,” in 2010 IEEE sixth international conference on e-Science, pp. 222–229, IEEE, 2010.

[39] B. Zhang, Y. Ruan, T.-L. Wu, J. Qiu, A. Hughes, and G. Fox, “Apply- ing twister to scientific applications,” in 2010 IEEE Second International Conference on Cloud Computing Technology and Science, pp. 25–32, IEEE, 2010.

[40] T. Gunarathne, T.-L. Wu, J. Qiu, and G. Fox, “Mapreduce in the clouds for science,” in 2010 IEEE second international conference on cloud computing technology and science, pp. 565–572, IEEE, 2010.

[41] S.-H. Bae, J. Y. Choi, J. Qiu, and G. C. Fox, “Dimension reduction and vi- sualization of large high-dimensional data via interpolation,” in Proceedings of the 19th ACM international symposium on high performance distributed computing, pp. 203–214, ACM, 2010.

[42] X. Qiu, J. Ekanayake, S. Beason, T. Gunarathne, G. Fox, R. Barga, and D. Gannon, “Cloud technologies for bioinformatics applications,” in Pro- ceedings of the 2nd Workshop on Many-Task Computing on Grids and Su- percomputers, p. 6, ACM, 2009.

[43] G. Fox, X. Qiu, S. Beason, J. Choi, J. Ekanayake, T. Gunarathne, M. Rho, H. Tang, N. Devadasan, and G. Liu, “Biomedical case studies in data inten- sive computing,” in IEEE International Conference on Cloud Computing, pp. 2–18, Springer, 2009.

[44] X. Qiu, G. Fox, H. Yuan, S.-H. Bae, G. Chrysanthakopoulos, and H. Nielsen, “Parallel data mining on multicore clusters,” in 2008 Seventh International Conference on Grid and Cooperative Computing, pp. 41–49, IEEE, 2008.

[45] X. Qiu, G. C. Fox, H. Yuan, S.-H. Bae, G. Chrysanthakopoulos, and H. F. Nielsen, “Performance of multicore systems on parallel data clustering with deterministic annealing,” in International Conference on Computational Science, pp. 407–416, Springer, 2008.

[46] X. Qiu, G. C. Fox, H. Yuan, S.-H. Bae, G. Chrysanthakopoulos, and H. F. Nielsen, “Parallel clustering and dimensional scaling on multicore systems,” HIGH PERFORMANCE COMPUTING & SIMULATION (HPCS 2008), p. 67, 2008.

[47] X. Qiu, G. C. Fox, H. Yuan, S.-H. Bae, G. Chrysanthakopoulos, and H. F. Nielsen, “High performance multi-paradigm messaging runtime integrating grids and multicore systems,” in Third IEEE International Conference on e-Science and Grid Computing (e-Science 2007), pp. 407–414, IEEE, 2007.

[48] X. Qiu and A. Jooloor, “Web service architecture for e-learning,” Journal of Systemics, Cybernetics and Informatics, vol. 3, no. 5, pp. 92–101, 2006.

[49] X. Qiu, S. Pallickara, and A. Uyar, “Making svg a web service in a message- based mvc architecture,” 2004.

[50] X. Qiu, “Building desktop applications with web services in a message- based mvc paradigm,” in Proceedings. IEEE International Conference on Web Services, 2004., pp. 765–768, IEEE, 2004.

[51] X. Qiu, B. Carpenter, and G. C. Fox, “Collaborative svg as a web service,” in SVG Open 2003 Conference and Exhibition, Vancouver, Canada, 2003.

[52] X. Qiu, B. Carpenter, G. C. Fox, et al., “Internet collaboration using the w3c document object model.,” in International Conference on Internet Computing, pp. 643–647, Citeseer, 2003.

[53] G. Fox, H. Bulut, K. Kim, S.-H. Ko, S. Lee, S. Oh, S. Pallickara, X. Qiu, A. Uyar, M. Wang, et al., “Collaborative web services and peer-to-peer grids,” SIMULATION SERIES, vol. 35, no. 1, pp. 3–12, 2003.

[54] J. Qiu, S. Kamburugamuve, H. Lee, J. Mitchell, R. Caldwell, G. Bullock, and L. Hayden, “Teaching, learning and collaborating through cloud com- puting online classes,”