uRiKA graph analytics appliance


In a research landscape dominated by vast and relentless influxes of data, finding hidden or unsuspected relationships in large data volumes is an increasingly difficult challenge. But finding it can be a game-changing event. On April 30, YarcData, a subsidiary of Cray, will present uRiKA, their Big Data mining solution, and provide illustrative examples of its use. uRiKA is an in-memory appliance for real-time graph analytics. 

The applications in graph problems are varied, ranging from security surveillance networks to Medicare fraud detection, drug discovery using a systems-biology approach, and social networks, and expand to many different domains of medicine and life and earth sciences research.

  • What: uRiKA: YarcData's graph analytics solution for Big Data mining
  • Who: YarcData; Steve Reinhardt, solution architect
  • Where: 402 Walter Library
  • When: April 30, 2013, 10:00-11:00 am
  • Contact: Anne-Françoise  Lamblin [lambl001@umn.edu]; MSI

If you would like to schedule time with the presenters during their visit, please use the contact above.

Keywords: graph analytics, graph database, semantic graph technologies, RDF, SPARQL, Big Data, data mining, uRiKA

To learn more about these graph analytics applications, please see references below .

For more information about Urika, visit YarcData's Products webpage or review some of its case files:

  1. Shahid H. Bokhari and Jon R. Sauer, Parallel Algorithms for Bioinformatics, invited chapter in Bioinformatics and Computational Biology, A. Zomaya, Editor. April 2006, Wiley.  
  2. Shahid Bokhari and Joel Saltz, Exploring the Performance of Massively Multithreaded Architectures, Technical Report OSUBMI-TR-2009-n01, Department of Biomedical Informatics, Ohio State University, January 20, 2009. Tech. Report version of above, contains some additional results.
  3. Shahid Bokhari and Daniel A. Janies, Reassortment Networks for Investigating the Evolution of Segmented Viruses,” appears in the IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 7 no. 2, pp. 288-298, April/June 2010
  4. Shahid Bokhari, Laura Pomeroy and Daniel Janies, Reassortment Networks and the Evolution of Pandemic H1N1 Swine-origin Influenza, IEEE/ACM Transactions on Computational Biology & Bioinformatics, vol. 9, no. 1, pp. 214-227, 2012. 
  5. Shahid Bokhari and Saniyah Bokhari, A Comparison of the Cray XMT and XMT-2, Concurrency and Computation: Practice and Experience, published online Aug 9, 2012. DOI: 10.1002/cpe.2909.  
  6. Shahid H. Bokhari, Umit V. Catalyurek and Metin N. Gurcan, Massively Multithreaded Maxflow for Image Segmentation on the Cray XMT-2, Technical Report No. 1, Algopath LLC, Cuperino, CA, March 28, 2013. 
  7. Steven J. Plimpton and Karen D. Devine, MapReduce in MPI for Large-scale Graph Algorithms, Journal Parallel Computing archive Volume 37 Issue 9, Pages 610-632,   September, 2011
  8. D. Ediger and D.A. Bader, Investigating Graph Algorithms in the BSP Model on the Cray XMT, 7th Workshop on Multithreaded Architectures and Applications (MTAAP), Boston, MA, May 24, 2013. (To be published)
  9. D.A. Bader, Exascale Analytics of Massive Social Networks, SIAM AN09 Minisymposium on High Performance Computing on Massive Real-World Graphs, 6-10 July 2009
  10. D.A. Bader, David Ediger, and Jason Riedy, Streaming Graph Analytics for Massive Graphs,  SIAM AN12 Minisymposium on Massive Graphs: Big Compute meets Big Data , 9-13 July 2012
  11. Papers based on C++: Scalable Multi-threaded Community Detection in Social Networks (Reidy, Bader, and Meyerhenke):  http://www.cc.gatech.edu/~bader/papers/ScalableCommunityDetection-MTAAP2012.pdf
  12. Papers based on RDF/SPARQL: Graph Clustering in SPARQL (the UCSB guys and me about the Challenge work, just an abstract): http://gauss.cs.ucsb.edu/publication/SIAM-DMA_uRiKA_PP.pdf