Now showing items 1-4 of 4
The fast multipole method at exascale
(Georgia Institute of Technology, 2013-11-26)
This thesis presents a top to bottom analysis on designing and implementing fast algorithms for current and future systems. We present new analysis, algorithmic techniques, and implementations of the Fast Multipole Method ...
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 ...
Middleware for large scale in situ analytics workflows
(Georgia Institute of Technology, 2016-11-17)
The trend to exascale is causing researchers to rethink the entire computa- tional science stack, as future generation machines will contain both diverse hardware environments and run times that manage them. Additionally, ...
Middleware for online scientific data analytics at extreme scale
(Georgia Institute of Technology, 2014-03-25)
Scientific simulations running on High End Computing machines in domains like Fusion, Astrophysics, and Combustion now routinely generate terabytes of data in a single run, and these data volumes are only expected to ...