A team at the Georgia Institute of Technology has received a $2.7 million award from the Defense Advanced Research Projects Agency (DARPA) to develop technology to help address the challenges of Big Data – data sets that are both massive and complex.
The contract is part of DARPA’s XDATA program, a four-year research effort to develop computational techniques and open-source software tools for processing and analysing data, motivated by defence needs. Georgia Tech was selected to perform research in the area of scalable analytics and data-processing technology.
The team will focus on producing new machine-learning approaches capable of analyzing very large-scale data. Team members will also pursue development of distributed computing methods that can process data-analytics algorithms very rapidly with a variety of systems, including supercomputers, parallel-processing environments and networked, distributed computing systems.
‘This award allows us to build on the foundations we’ve already established in large-scale data analytics and visualisation,’ said Richard Fujimoto, leader of the Georgia Tech team. ‘The algorithms, tools and other technologies that we develop will all be open source, to allow them to be customised to address new problems arising in defence and other applications.’
The award is part of a $200 million multi-agency federal initiative for big-data research and development. It aims to improve the ability to extract knowledge and insights from the nation’s fast-growing volumes of digital data.
This story appears here as part of a cross-publishing agreement with Scientific Computing World.
Based on the most recent release of the 
Over at 
The HPC Advisory Council has posted the 
