Contestants Demonstrate the Value of Discovering Hidden Insights in Big Data across Industries
PLEASANTON, CA -- YarcData, a Cray company dedicated to providing "Big Data" graph-analytic solutions to enterprises, has announced the winners of the YarcData Graph Analytics Challenge showcasing the increasing applicability and adoption of graph analytics in discovering unknown relationships in Big Data. Submissions included an innovative range of applications across a broad variety of sectors including crime prediction, social science, life science and sports performance.
Dr. Brady Bernard, Andrea Eakin, and Dr. Ilya Shmulevich, of The Institute for Systems Biology (ISB), were awarded first prize and will split $70,000 for their winning entry researching more than 25 different types of cancers and thousands of patients to gain insight into the biological networks that are disrupted or altered within a given cancer type and to identify potentially potent approved drugs that could be repurposed for the given cancer.
The winning solution combined unstructured data from medical articles with structured data from genomic and proteomic databases. Using YarcData's uRiKA graph analytics appliance, this team combined these disparate data sources into a powerful tool for scientific discovery enabling researchers to formulate a theory, quickly test it against all available data, and interactively refine the hypothesis.
"In the amount of time it takes to explore one hypothesis, we can now explore thousands of hypotheses, massively improving our success rate," said Dr. Ilya Shmulevich, Professor, Institute for Systems Biology. "Our queries needed to cross multiple genes and diverse cancer datasets, producing results in seconds to queries several pages long on graphs of billions of edges. Before YarcData, it has not been possible to perform this type of large scale analysis and identify complex multivariate relationships in heterogeneous data."
The winning entries were selected by a panel of judges made up of Big Data industry analysts, experts on semantic technology, and YarcData customers based on a set of criteria that includes the business and/or human impact, complexity, scalability and performance, and innovation.
"The complexity of discovery needs and the potential for a positive impact on society elevated the winning submission in a very competitive group of entrants," said contest judge Dr. Bruce Hendrickson, Senior Manager for Computational Sciences and Mathematics at Sandia National Laboratories and Affiliated Professor of Computer Science at the University of New Mexico. "The winning entry demonstrated classic features of Big Data problems: a large volume of complex information from a variety of disparate sources and a need to manage data input and output at a high velocity. The team's submission exemplified the power of graph analytics for gaining insight into difficult knowledge-discovery problems."
Second place was awarded to Adam Lugowski, Dr. John Gilbert, and Kevin Dewesse, of the University of California at Santa Barbara and they will split $13,000 for their efforts investigating the causes of autism by understanding clusters of precursors. Third place and $8,000 was awarded to Dr. Abraham Flaxman, of the University of Washington Institute for Health Metrics and Evaluation, for his model predicting risk and mortality in the 30 days following a heart attack, enabling high-risk patients to be identified for special attention.
"Our objective with the Graph Analytics Challenge was to showcase the power of graph analytics and its growing adoption for discovering new insights in Big Data," said Arvind Parthasarathi, president of YarcData. "We were very impressed with the quality of the solutions submitted and the wide cross section of industries the solutions represent. We thank all the participants and congratulate the winners and finalists."
The other finalists were awarded $3,000 prizes for their entries, which included:
- Erik Celentano, Dr. Gary Shiffman, Dr. Danielle Sandler, of Giant Oak: Predicting future crime based on structural, institutional, and demographic make-up of neighborhoods where crime occurs;
- Vince Gennaro, of Diamond Dollars: Analyzing pitcher-batter outcome data in baseball to determine if there is a relationship between a hitter's performance against varying quality levels of pitching;
- Dominic DiFranzo, Bassem Makmi, Qingpeng Zhang, of the Rensselaer Polytechnic Institute: Conducting large-scale social network analysis to determine the impact of team behavior/collaboration by using gaming data.
For more information on the contest, please visit: http://yarcdata.com/graph-analytic-challenge.html.
About the uRiKA Appliance
The uRiKA system is a purpose-built appliance for graph analytics featuring graph-optimized hardware that provides up to 512 terabytes of global shared memory, massively-multithreaded graph processors supporting 128 threads/processor, and highly scalable I/O with data ingest rates of up to 350 terabytes per hour — and an RDF/SPARQL database optimized for the underlying hardware enabling applications to interact with the appliance using industry standard interfaces. The uRiKA system complements an existing data warehouse or Hadoop cluster by offloading graph workloads and interoperating within the existing analytics workflow. Subscription pricing for on-premise deployment of the appliance eases the adoption of the uRiKA system into existing IT environments.
YarcData, a Cray company, delivers business-focused real-time graph analytics for enterprises to gain business insight by discovering unknown relationships in Big Data. Customers include the Canadian government, Mayo Clinic, Noblis, Pittsburgh Supercomputing Center, Sandia National Laboratories, and the United States government, among others. YarcData is based in the San Francisco bay area.
Cray provides innovative supercomputing systems and solutions enabling scientists and engineers in industry, academia and government to meet existing and future simulation and analytics challenges. Leveraging 40 years of experience in developing and servicing the world's most advanced supercomputers, Cray offers a comprehensive portfolio of supercomputers and Big Data solutions. Cray's Adaptive Supercomputing vision is focused on delivering innovative next-generation products that integrate diverse processing technologies into a unified architecture, allowing customers to surpass today's limitations and meeting the market's continued demand for realized performance.