Correlation Aware Optimizations for Analytic Databases

Hideaki Kimura, Brown University

1:00pm Friday 9 March 2012, ITE 325b, UMBC

Recent years have seen that the analysis of large data-sets is crucially important in a wide range of business, governmental, and scientific applications. For example, research projects in astronomy need to analyze petabytes of image data taken from telescopes. Providing a fast and scalable analytical data management system for such users has become increasingly important.

The major bottlenecks for analytics on such big data are disk- and network-I/O. Because the data is too large to fit in RAM, each query causes substantial disk I/O. Traditional database systems provide indexes to speed up disk reads, but many analytic queries do not benefit from indexes because data is scattered over a large number of disk blocks and disk seeks are prohibitively expensive. Furthermore, such huge data sets need to be partitioned and distributed over hundreds or many thousands of nodes. When a query requires more than one data at once, such as a query involving a JOIN operation, the data management system must transmit a large amount of data over the network. For example, the Shuffle phase in Map-Reduce systems copies file blocks over the network and causes a significant bottleneck in many cases.

Our approach to tackling these challenges in big data analytics is to exploit correlations. I will describe our correlation-aware indexing, replication, and data placement which make big data analytics faster and more scalable.

Finally, if time allows, I will also introduce another on-going project to develop a scalable transactional processing system on modern hardware in collaboration with Hewlett-Packard Laboratories.

Hideaki Kimura is a doctoral candidate in the Computer Science Department at Brown University. His main research interests are in data management systems. His dissertation research with Prof. Stan Zdonik is on correlation-based optimizations for large analytic databases. He also worked on transaction processing systems exploiting modern hardware at HP Labs.

Host: Anupam Joshi
See http://csee.umbc.edu/talks for more information

Interactive visual computing for knowledge discovery
in science, engineering and training

Dr. Jian Chen
University of Southern Mississippi

1:00pm Wednesday 7 March 2012, ITE 325b UMBC

Advances in simulations and lab experiments are producing huge datasets at unprecedented rates, and deriving meanings from these data will have far-reaching impacts on our lives in many areas of science, engineering, and medicine. Visualization and interactive computing provide great tools for exploiting these data in scientific discovery and engineering innovations. A limiting factor in the scientific use of visualization tools is the lack of guiding principles to identify and assess visualization methods that are helpful in scientific tasks. In this talk, I present research designed to advance knowledge discovery through the design and evaluation of interactive visualizations. Experiments on image illumination and density are described that successfully address this limitation in brain imaging for medical diagnoses. I also present the theoretical foundations that have led to the various choices in visualization design. In the second part of the talk, I argue that most existing tools designed for scientific discovery fail to address the dynamic nature of the discovery workflow. I present a new visualization tool, VisBubbles, that integrates programming, visualization, and interaction in one environment to create fluid workflows in which new hypotheses can be tested efficiently. VisBubbles augments interactive computing and analysis of time-varying motion data of bat flights by enabling dynamic displays, thus facilitating scientists' quest for new knowledge. I present the design methods we have followed in our long-term collaboration with biologists and engineering scientists on motion analysis. Finally, I present future work I envision in interactive visualization that will be critical in developing future visualization tools for science, engineering, and training.

Jian Chen is an assistant professor in the School of Computing at the University of Southern Mississippi. She is the founder and director of Interactive Visual Computing Lab. Her research is in the broad area of interaction and visualization, with current focuses on the emerging field of scientific visualization theory and workflow analysis. She has published numerous articles in top journals and international conferences. Her panel on combining human-centered computing and scientific visualization received honorable mention at the 2007 IEEE Visualization Conference. She was a postdoc at Brown University with Drs. David H. Laidlaw (CS) and Sharon Swartz (BioMed) from 2006 to 2009. She has a Ph.D. degree in Computer Science from Virginia Tech and Master’s degrees in both Computer Science and Mechanical Engineering. Her research has been funded by DHS and NSF.

Host: Penny Rheingans

See here for more information

• Two years (min) of engineering coursework (Mechanical Engineering preferred)
• Familiarity with electronic design tools (AutoCAD, MDT, Inventor) a plus
• Excellent communication skills
• Familiarity with LEAN, Six Sigma a plus
• Familiarity with technical writing, social media, sales/marketing materials desired

EE Graduate Seminar

Spectrum Wars: LightSquared vs. GPS

Professor Chuck LaBerge
Professor of the Practice, CSEE Dept/UMBC

11:30am-12:45pm Friday, 2 March 2012, ITE 231

The radio-frequency spectrum is a limited resource. Within the US, commercial use of the spectrum is administered by the Federal Communications Commission (FCC), while government use of the spectrum is administered by the National Telecommunications and Information Administration. Currently, the regulatory community is locked in a battle about spectrum utilization in the vicinity of 1.5 GHz. This struggle pits millions of users of GPS technology for position and time information against technical innovators desiring to bring 4G wireless communications to millions of users in underserved populations. So who wins the spectrum wars?

The talk will outline the technologies involved, and provide a time-line of the regulatory actions to date. There are some innovative things going on here, and some simple analysis will show why there are points of contention. A final resolution cannot be provided at this time, because the issue is currently an open discussion in FCC. And, as might expected, there are financial and political ramifications as well.

This talk will provide an interesting insight into how the 'real world' works.

Dr. LaBerge is Professor of the Practice of Electrical and Computer Engineering in the CSEE at UMBC, where he teaches a wide variety of courses ranging from Introductory Circuits to Error Correcting Codes. From 1975-2008, he was employed by Bendix, which became AlliedSignal, which became Honeywell through a series of corporate mergers. He retired in July 2008 as the Senior Fellow for Communications, Navigation, and Surveillance in Honeywell's Aerospace Research and Technology Center.

Dr. LaBerge has worked on precision landing systems and a wide variety of aeronautical radios and applications. He's recognized as an expert in issues involving interference to aeronautical systems. His technical, writing, and editorial contributions have received numerous citations from regulatory bodies, and he was the winner of the Best Paper of Conference at the 2000 IEEE/AIAA Digital Avionics Systems Conference.

Dr. LaBerge is a Senior Member of IEEE, a member of Tau Beta Pi, and an inductee in the Order of the Engineer. He received his BES-EE and MSE-EE, degrees, both with Honors, from The Johns Hopkins University and the PhD. in Electrical Engineering from UMBC. His three kids are older than his students. He's been married to his patient wife for almost 38 years.

Host: Prof. Joel M. Morris

Using Static Analysis to Diagnose
Misconfigured Open Source Systems Software

Ariel Rabkin, UC Berkeley

1:00pm Monday 5 March 2012, ITE 325b UMBC

Ten years ago, few software developers worked on distributed systems. Today, developers often run code on clusters, relying on large open-source software stacks to manage resources. These systems are challenging to configure and debug. Fortunately, developments in program analysis have given us new tools for managing the complexity of modern software. This talk will show how static analysis can help users configure their systems. I present a technique that builds an explicit table mapping a program's possible error messages to the options that might cause them. As a result, users can get immediate feedback on how to resolve configuration errors.

Ari Rabkin is a PhD student in Computer Science at UC Berkeley working in the AMP lab. His current research interest is the software engineering and administration challenges of big-data systems. He is particularly interested in applying program analysis techniques to tasks like log analysis and configuration debugging. His broader interests focus on systems and security, including improving system usability by making systems easier to understand, the connections between computer science research and technology policy, developing program analysis techniques that work acceptably well on large, complex, messy software systems.

Host: Anupam Joshi
See http://csee.umbc.edu/talks for more information

UMBC has earned an honorable mention on The Princeton Review’s recently released list: “Top Schools to Study Video Game Design for 2012.” The recognition places UMBC among schools like Georgia Institute of Technology, UC Santa Cruz, and Northeastern University.

Released annually, the list features 50 schools from around the country, including their “top ten” undergraduate and graduate schools in this category. This year, the University of Southern California secured first place for their undergraduate game design program. The rankings were based on a survey administered by The Princeton Review during the 2011-2012 academic year that consulted administrators at 150 schools and universities. The winning schools were judged on the quality of their curriculum, faculty, facilities, and infrastructure, as well as their scholarship, financial aid, and career opportunities.

“We salute the schools on our list this year for their commitment to this burgeoning field and the innovative programs they offer. For students aspiring to work in this more than $10.5 billion industry and for the companies that will need their creative talents and skills, we hope this project will serve as a catalyst for many rewarding connections,” says Robert Franek, The Princeton Review’s Senior VP/Publisher in a press release.

Both UMBC’s Computer Science and Electrical Engineering Department and its Visual Arts Department offer programs for students interested in pursuing a career in video game development. Artists can concentrate on “Animation and Interactive Media,” while computer programmers can pursue the “Game Development” track within the Computer Science major. In addition, UMBC has a Game Development club, and has been a host site of the International Development Association’s Global Game Jam for the past four years.

To see a comprehensive list of winners, visit The Princeton Review’s website.

The buzz about driverless cars erupted after Google received a patent for the technology in December of last year. Since then, the project has been steadily moving forward. A few days ago, Google started testing their vehicles on Nevada roads, following approval by the state’s Legislative Commission. With the inevitability of autonomous transportation creeping closer, measures to ensure its realization are being pursued by more companies than just Google.

Peter Stone, a professor of computer science at the University of Texas at Austin, and his team are working on developing a “smart” intersection that would manage the flow of driverless cars, reports techworld.com.

According to Stone’s project, intersections would be equipped with a manager that would coordinate traffic in an efficient and mathematical way. Techworld reports:

‘"When a car gets close to the intersection, it calls ahead and says, 'I want to go through the intersection.' The intersection manager says either yes or no. It keeps track of the reservations it grants and makes sure it doesn't give permission to other cars that would conflict with them," Stone said.’

To learn more, check out the full article: “Scientists develop computer-controlled intersections for self-driving cars.”