Today's "connect anytime and anywhere" society based on the use of digital technologies is fueling tremendous data growth and transforming the way our business, science, and digital technology-based world functions. Data in the terabytes range are not uncommon today and are expected to reach petabytes for many application domains in science, engineering, business, bioinformatics, and medicine in the near future. Ultra-scale refers to the two to three orders of magnitude increase in data sizes, computing power, and complexity of data compared to what is considered today. As data becomes so pervasive, assurance, trust and security of information becomes of paramount importance. Secure computing, therefore, must be considered as an important parameter in any research dealing with ultra-scale computing.
The goal of the Center for Ultra-scale Computing and Information Security (CUCIS) is to conduct highly innovative research in many synergistic areas of ultra-scale computing and information technologies. Furthermore, the goal of the center is to foster and enable inter-disciplinary research in computing technologies that scale to these levels. The CUCIS is directed by Prof. Alok Choudhary, and is presently supported by the NSF, DOE, Sandia National Labs, NASA, and Intel. To learn more, please use the navigation bar at the top of the page, or go directly to descriptions of our various research projects, a complete list of our publications, or more information about the group members.
Software Developed by the Center:
- Data Mining
- NU-MineBench -- a collection of data mining algorithms and applications in sequential and parallel
- Parallel Data Clustering Algorithms -- a collection of massively parallel data clustering algorithms, including DBSCAN, OPTICS, and PINK
- Fast Max Clique Finder -- a sotfware suite to find the maximum cliques of large sparse graphs. See a use case in social network data.
- Parallel I/O
- Parallel netCDF -- a parallel I/O library for accessing netCDF files
Postdoctoral Researcher Opportunity:
- We are looking for postdoctoral associates to conduct research in the areas of data ming, database management, and high-performance computing. See the Job Posting for contact information.
Graduate Student Research Assistantship:We are looking for graduate students who are interested in pursuing a Ph.D. degree in the following areas:
- Computational validation and error detection -- Trusting scientific applications requires guaranteeing the validity of computed results. Currently known validation techniques cover only a fraction of the possible corruptions that numerical simulation and data analytics applications may suffer during execution. As science processes grow in size and complexity, the reliability and validity of their constituent steps is increasingly difficult to ascertain. The student will work on an NSF-funded project called ALETHEIA to research methods for detecting and correcting errors in the results of scientific applications. The approach involves approximate comparison of the compressed results of the scientific application with a surrogate function of lower complexity. The project explores the detection performance of surrogate functions, lossy compressors, and approximate comparison techniques. The project also explores how to select the surrogate, lossy compression, and approximate functions to optimize objectives and constraints set by the users. The student will collaborate with computer and computational scientists at the Mathematics and Computer Science division of Argonne National Laboratory in suburban Chicago (http://www.mcs.anl.gov).
- High-performance computing (theory and programming in MPI, OpenMP, GPU) and its application in Astrophysics. The student will work on an NSF-funded project in the field of large-scale N-body simulations and will be co-advised by Prof. Fred Rasio at Department of Physics.
- Esteban Rangel presented the paper titled "Parallel DTFE Surface Density Field Reconstruction" in the 2016 IEEE International Conference on Cluster Computing, which is awarded the best paper of the conference. The paper is co-authored by Esteban Rangel, Nan Li, Salman Habib, Tom Peterka, Ankit Agrawal, Wei-Keng Liao, and Alok Choudhary.
- The NSF features the expeditions project in an article titled: "Using data to better understand climate change" (Dr. Alok Choudhary is the project co-PI.)
- Diana Palsetia was awarded a GHC Scholarship Grant to attend the 2014 Grace Hopper Celebration of Women in Computing. (scholar page)
- Prof. Choudhary, has been quoted in a recent HPCWire article, titled, "DOE Exascale Roadmap Highlights Big Data." As Choudhary observed of the report, titled, Big Data and Scientific Discovery, “Very few large scale applications of practical importance are NOT data intensive.” Read More
- 4C, in partnership with Facebook has conducted a study to show the relationship between public Facebook behavioral data and television broadcast programming. By analyzing public Facebook data, 4C is helping networks make intelligent programming decisions and enabling brands to more strategically place relevant advertisements both on television and on Facebook. Read More
- Prof. Alok Choudhary has received major funding for his big data startup, 4C. The amount of $5 million from Chicago-based venture fund Jump Capital was awarded to the Social Intelligence Company based on 4C's platforms application of algorithms. Based on decades of research by Prof. Choudhary, these algorithm mine social-media data around the globe to help advertisers target their campaigns on television, Twitter, Facebook and other media channels. Read More
- Prof. Alok Choudhary gave a plenary talk, "Big Data + Big Compute = An Extreme Scale Marriage for Smarter Science?" at the Supercomputing Conference on Thursday, Nov 21, 2013, at the Denver Convention Center. [slides] (25 MB) Read More
- Parallel netCDF was used in petascale simulation of hurricane Sandy running on 437,760 computer cores of the Cray XE6 Blue Waters supercomputer at the National Center for Supercomputing Applications.
- Md. Mostofa Ali Patwary, Diana Palsetia, Ankit Agrawal, Wei-keng Liao, Fredrik Manne, and Alok Choudhary. "Scalable Parallel OPTICS Data Clustering Using Graph Algorithmic Techniques" has been published in the proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November 17-22, 2013 in Denver, Colorado.
- Zhengzhang Chen, Yusheng Xie, Yu Cheng, Kunpeng Zhang, Ankit Agrawal, Wei-keng Liao, Nagiza Samatova, Alok Choudhary, "Forecast Oriented Classification of Spatio-Temporal Extreme Events" has been published in the proceedings of the 23rd International Joint Conference on Artificial Intelligence to be held in Beijing, China, on August 3-9, 2013.
- Yusheng Xie, Zhengzhang Chen, Kunpeng Zhang, Yu Cheng, Ankit Agrawal, Wei-keng Liao, Alok Choudhary, "Detecting and Tracking Disease Outbreaks in Real-time through Social Media" has been published in the proceedings of the 23rd International Joint Conference on Artificial Intelligence to be held in Beijing, China, on August 3-9, 2013.
- Twitter API Partner Voxsup Applies Data Science to Social Media
- Zhengzhang Chen, John Jenkins, Jinfeng Rao, Alok Choudhary, Fredrick Semazzi, Anatoli V Melechko, Vipin Kumar, and Nagiza F Samatova, "Automatic Detection and Correction of Multi-class Classification Errors Using System Whole-part Relationships" has been published in the proceedings of the 13th SIAM International Conference on Data Mining, May 2-4, 2013 in Austin, Texas.
- Yusheng Xie, Zhengzhang Chen, Kunpeng Zhang, Md Mostofa Ali Patwary, Yu Cheng, Haotioan Liu, Ankit Agrawal, and Alok Choudhary, "Graphical Modeling of Macro Behavioral Targeting in Social Networks" has been published in the proceedings of the 13th SIAM International Conference on Data Mining, May 2-4, 2013 in Austin, Texas.
- Jason Scott Mathias, Ankit Agrawal, Joe Feinglass, Andrew J Cooper, David William Baker, Alok Choudhary, "Development of a 5 year life expectancy index in older adults using predictive mining of electronic health record data" has been published in the Journal of the American Medical Informatics Association, (04/2013), (pdf), (supplement).
- Daniel Honbo, Amit Pande, Alok Choudhary, "FPGA Architecture for Pairwise Statistical Significance Estimation", has been published in The International Journal of High Performance Systems Architecture. Link
- Bharath Pattabiraman, Stefan Umbreit, Wei-keng Liao, Alok Choudhary, Vassiliki Kalogera, Gokhan Memik, Frederic A. Rasio, "A Parallel Monte Carlo Code for Simulating Collisional N-body Systems", has been published in The Astrophysical Journal Supplement, Volume 204, Issue 2, article id. 15, 16 pp. PDF
- Tasty Trade, a real financial network interviews Alok Choudhary (Interview).
- EECS Graduate Student Poster Fair -- Kathy Lee presented "Real-Time Flu Surveillance using Twitter Data". Diana Palsetia presented "User-Interest based Community Extraction in Social Networks". Professor William Hendrix was a judge.