Now showing items 1-4 of 4
High performance computing for irregular algorithms and applications with an emphasis on big data analytics
(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 ...
Graph analysis of streaming relational data
(Georgia Institute of Technology, 2018-04-13)
Graph analysis can be used to study streaming data from a variety of sources, such as social networks, financial transactions, and online communication. The analysis of streaming data poses many challenges, including dealing ...
Graph analysis combining numerical, statistical, and streaming techniques
(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 ...
Algorithm design on multicore processors for massive-data analysis
(Georgia Institute of Technology, 2010-06-28)
Analyzing massive-data sets and streams is computationally very challenging. Data sets in systems biology, network analysis and security use network abstraction to construct large-scale graphs. Graph algorithms such as ...