Upcoming seminars

Upcoming Seminars
Fri
10/31/2014
(today)
3:00pm
Defense: Dissertation
High Performance Spatial Query Processing for Large Scale Spatial Data Warehousing
Ablimit Aji, Emory University
Contact: James Lu, jlu@mathcs.emory.edu
Venue: Mathematics and Science Center, Room W303
Support of high performance queries on large volumes of spatial data have become important in many application domains, including geowspatial problems in numerous fields, location based services, geo-social networks, and emerging scientific applications that are increasingly data- and compute-intensive. There are two major challenges for managing and querying massive spatial data: the explosion of spatial data, and the high computational complexity of spatial queries due to the multi-dimensional nature of spatial analytics. High performance computing capabilities are fundamental to efficiently handling of massive spatial datasets. MapReduce based computing model provides a highly scalable, reliable, elastic and cost effective framework for processing massive data on a cluster or cloud environment. While the MapReduce model fits nicely with large scale problems through data partitioning, spatial queries and analytics are intrinsically complex to fit into the MapReduce model easily. Meanwhile, hybrid systems combining CPUs and GPUs are becoming commonly available in commodity clusters, but the computing capacity of such systems is often underutilized. Providing new spatial querying and analytical methods to run on such architecture requires us to answer several fundamental research questions that are of practical importance. The goal of my dissertation is to create a framework with new systematic methods to support high performance spatial queries for spatial big data on MapReduce and CPU-GPU hybrid platforms, driven by real-world use cases. Towards that end, we have researched multi-level parallelism methods of spatial queries running on these platforms. Specifically, we have conducted following studies: 1) create new spatial data processing methods and pipelines with spatial partition level parallelism through a simple programming model MapReduce and propose multi-level indexing methods to accelerate spatial data processing, 2) develop two critical components to enable data parallelism: effective and scalable spatial partitioning in MapReduce (pre-processing), and query normalization methods for partition effect, 3) integrate GPU-based spatial operations into MapReduce pipelines 4) investigate optimization methods for data skew mitigation, and CPU/GPU resource coordination in MapReduce, and 5) support declarative spatial queries for workload composition, and create a query translator to automatically translate the queries into MapReduce programs. Consequently, we have developed Hadoop-GISb a MapReduce based high performance spatial querying system for spatial data warehousing. The system supports multiple types of spatial queries on MapReduce through spatial partitioning, implicit parallel spatial query execution on MapReduce, and effective methods for amending query results through handling bound- ary objects. Hadoop-GIS utilizes global partition indexing and customizable on demand local spatial indexing to achieve efficient query processing. Hadoop-GIS is integrated into Hive to support declarative spatial queries with an integrated architecture. The systems and developed approaches are released as an open source software package for use.
Mon
11/03/2014
(in 3 days)
4:00pm
Seminar: Combinatorics
Semidefinite programming in extremal graph theory
Florian Pfender, The University of Colorado, Denver
Contact: Dwight Duffus, dwight@mathcs.emory.edu
Venue: Mathematics and Science Center, Room W302
Razborov developed in 2007 the theory of flag algebras. Within this theory, densities of small substructures in large combinatorial structures can be described and computed. His so called "plain flag algebra method" uses semidefinite programming to optimally combine a large number of true inequalities to get bounds on densities in many contexts.\\ \\ One context the method can be used in is the inducibility of graphs. We are looking to maximize the number of induced copies of a given small graph in a very large graph. Whenever the extremal graph to a problem has a simple blow-up structure, the plain method often works very well. But when the structure is more complicated, the bounds tend to get weaker. We recently expanded the plain method to be able to deal with an iterated blow-up structure, which often appears as extremal construction for inducibility questions.
Tue
11/04/2014
(in 4 days)
1:00pm
Seminar: Combinatorics
Distinct edge weights on graphs
Michael Tait, The University of California, San Diego
Contact: Vojtech Rodl, rodl@mathcs.emory.edu
Venue: Mathematics and Science Center, Room E408
A Sidon set is a subset of an abelian group which has the property that all of its pairwise sums are distinct. Sidon sets are well-studied objects in combinatorial number theory and have applications in extremal graph theory and finite geometry. Working in the group of integers with multiplication, Erdos showed that one cannot find a Sidon set that is asymptotically denser than the primes. In this talk, we show that one can obtain the same result with a much weaker restriction than requiring a Sidon set. This complements work of Bollobas and Pikhurko from 2004. We also discuss an open problem that they posed, with some ideas for how to attack it. This is joint work with Jacques Verstraete.
Tue
11/04/2014
(in 4 days)
4:00pm
Seminar: Algebra
Joint Athens-Atlanta number theory seminar (at Georgia Tech)
Arul Shankar and Wei Zhang,
Venue:
Mon
11/10/2014
(in 10 days)
4:00pm
Seminar: Analysis and Differential Geometry
Mathematical problems in visual sciences
Professor Jacob Rubinstein, Israel Institute of Technology - Technion
Contact: Vladimir Oliker, oliker@mathcs.emory.edu
Venue: Mathematics and Science Center, Room W303
This talk should be of general interest to mathematicians and researchers in visual science and ophthalmology. It will be accessible to graduate students.
Tue
11/11/2014
(in 11 days)
4:00pm
Seminar: Algebra
Monstrous Moonshine, Umbral Moonshine and the Conway Group
John Duncan, Case Western
Contact: David Zureick-Brown, dzb@mathcs.emory.edu
Venue: Mathematics and Science Center, Room W306
Monstrous moonshine attaches distinguished modular functions to elements of the monster sporadic simple group. Umbral moonshine is analogous, but involves mock modular forms in place of modular functions, and certain subgroups of the Conway group take on the role of the monster. Ono--Rolen--Trebat-Leder established the first result demonstrating that monstrous and umbral moonshine are directly related. I will describe recent, related joint work with S. Mack-Crane that further supports the view that monstrous and umbral moonshine have a common origin: we construct the natural analogue of the moonshine module for Conway's group, and show that it can be used to recover mock modular forms arising in the pure A type cases of umbral moonshine.