Now showing items 43-62 of 110

    • Generalized N-body problems: a framework for scalable computation 

      Riegel, Ryan Nelson (Georgia Institute of Technology, 2013-08-26)
      In the wake of the Big Data phenomenon, the computing world has seen a number of computational paradigms developed in response to the sudden need to process ever-increasing volumes of data. Most notably, MapReduce has ...
    • Graph analysis combining numerical, statistical, and streaming techniques 

      Fairbanks, James Paul (Georgia Institute of Technology, 2016-03-31)
      Graph analysis uses graph data collected on a physical, biological, or social phenomena to shed light on the underlying dynamics and behavior of the agents in that system. Many fields contribute to this topic including ...
    • Graph-based algorithms and models for security, healthcare, and finance 

      Tamersoy, Acar (Georgia Institute of Technology, 2016-04-15)
      Graphs (or networks) are now omnipresent, infusing into many aspects of society. This dissertation contributes unified graph-based algorithms and models to help solve large-scale societal problems affecting millions of ...
    • Graphical Models for the Internet 

      Smola, Alexander (Georgia Institute of Technology, 2011-04-29)
      In this talk I will present algorithms for performing large scale inference using Latent Dirichlet Allocation and a novel Cluster-Topic model to estimate user preferences and to group stories into coherent, topically ...
    • Gravity's Strongest Grip: A Computational Challenge 

      Shoemaker, Deirdre (Georgia Institute of Technology, 2010-10-22)
      Gravitational physics is entering a new era driven by observation that will begin once gravitational-wave interferometers make their first detections. In the universe, gravitational waves are produced during violent events ...
    • High performance computing for irregular algorithms and applications with an emphasis on big data analytics 

      Green, Oded (Georgia Institute of Technology, 2014-03-31)
      Irregular algorithms such as graph algorithms, sorting, and sparse matrix multiplication, present numerous programming challenges, including scalability, load balancing, and efficient memory utilization. In this age of Big ...
    • High-performance algorithms and software for large-scale molecular simulation 

      Liu, Xing (Georgia Institute of Technology, 2014-12-17)
      Molecular simulation is an indispensable tool in many different disciplines such as physics, biology, chemical engineering, materials science, drug design, and others. Performing large-scale molecular simulation is of great ...
    • High-performance computing for massive graph analysis 

      Bader, David A. (Georgia Institute of Technology, 2010-10-30)
    • High-performance-computing challenges for heart simulations 

      Fenton, Flavio H. (Georgia Institute of Technology, 2012-08-31)
      The heart is an electro-mechanical system in which, under normal conditions, electrical waves propagate in a coordinated manner to initiate an efficient contraction. In pathologic states, propagation can destabilize and ...
    • How much (execution) time and energy does my algorithm cost? 

      Vuduc, Richard W. (Georgia Institute of Technology, 2012-08-24)
      When designing an algorithm or performance-tuning code, is time-efficiency (e.g., operations per second) the same as energy-efficiency (e.g., operations per Joule)? Why or why not? To answer these questions, we posit a ...
    • Implementation and analysis of a parallel vertex-centered finite element segmental refinement multigrid solver 

      Henneking, Stefan (Georgia Institute of Technology, 2016-04-28)
      In a parallel vertex-centered finite element multigrid solver, segmental refinement can be used to avoid all inter-process communication on the fine grids. While domain decomposition methods generally require coupled ...
    • Influence modeling in behavioral data 

      Li, Liangda (Georgia Institute of Technology, 2015-05-15)
      Understanding influence in behavioral data has become increasingly important in analyzing the cause and effect of human behaviors under various scenarios. Influence modeling enables us to learn not only how human behaviors ...
    • Integration of computational methods and visual analytics for large-scale high-dimensional data 

      Choo, Jae gul (Georgia Institute of Technology, 2013-07-02)
      With the increasing amount of collected data, large-scale high-dimensional data analysis is becoming essential in many areas. These data can be analyzed either by using fully computational methods or by leveraging human ...
    • Intelligent hazard identification: Dynamic visibility measurement of construction equipment operators 

      Ray, Soumitry J. (Georgia Institute of Technology, 2014-03-26)
      Struck-by fatalities involving heavy equipment such as trucks and cranes accounted for 24.6% of the fatalities between 1997-2007 in the construction industry. Limited visibility due to blind spots and travel in reverse ...
    • The Joy of PCA 

      Vempala, Santosh (Georgia Institute of Technology, 2010-09-17)
      Principal Component Analysis is the most widely used technique for high-dimensional or large data. For typical applications (nearest neighbor, clustering, learning), it is not hard to build examples on which PCA "fails." ...
    • Leveraging Memory Mapping for Fast and Scalable Graph Computation on a PC 

      Lin, Zhiyuan; Chau, Duen Horng (Polo) (Georgia Institute of Technology, 2013-08)
      Large graphs with billions of nodes and edges are increasingly common, calling for new kinds of scalable computation frameworks. Although popular, distributed approaches can be expensive to build, or require many resources ...
    • Load-Balanced Bonded Force Calculations on Anton 

      Franchetti, Franz (Georgia Institute of Technology, 2010-03-15)
      Spiral (www.spiral.net) is a program and hardware design generation system for linear transforms such as the discrete Fourier transform, discrete cosine transforms, filters, and others. We are currently extending Spiral ...
    • Mage: Expressive Pattern Matching in Richly-Attributed Graphs 

      Pienta, Robert; Tamersoy, Acar; Tong, Hanghang; Chau, Duen horng (Polo) (Georgia Institute of Technology, 2013)
      Given a large graph with millions of nodes and edges, say a social graph where both the nodes and edges can have multiple different kinds of attributes (e.g., job titles, tie strengths), how do we quickly find matches ...
    • Magnetic Resonance Imaging of the Brain 

      Hu, Xiaoping (Georgia Institute of Technology, 2012-10-12)
      Magnetic Resonance Imaging (MRI) has become a powerful, indispensable, and ubiquitously used methodology in neuroimaging. In particularly, functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) ...
    • Metanumerical computing for partial differential equations: the Sundance project 

      Kirby, Robert C. (Georgia Institute of Technology, 2010-10-29)
      Metanumerical computing deals with computer programs that use abstract mathematical structure to manipulate, generate, and/or optimize compute-intensive numerical codes. This idea has gained popularity over the last decade ...