The upcoming exascale generation of supercomputers will be powerful enough to calculate 1018 operations per second, but matching those machines with the complex dataset of the petascale (1015 elements) presents multiple challenges.
George Slota, a computer scientist at Rensselaer Polytechnic Institute, has been granted a $488,066 National Science Foundation Faculty Early Career Development (CAREER) award to develop approaches to the problem.
"How do we best understand and get insight from this kind of data? To do that, we have to map the data to the hardware, with consideration of the algorithm itself," says Slota. "Each aspect is fairly challenging because of the complexity of the data and the complexity of modern hardware."
With the grant, Slota will develop a "graph layout," a high-quality and scalable means of partitioning, ordering, and storing the data given the data type, the relevant algorithms, and the hardware platform that will be used to analyze it.
Slota will work to map the data and the algorithmic analysis method to the equally complex and irregular architecture of the supercomputer, with its network of interconnected computers, processors, and multiple levels of memory.
From Rensselaer Polytechnic Institute
View Full Article