IBM analytics to plumb universe's secret

IBM analytics to plumb universe's secret

PORTLAND, Ore.—IBM will harness water-cooled 3-D chip sets to plumb the secrets of the universe by analyzing exabytes (billion gigabytes) of data streaming in from the world's largest radio telescope to be constructed in 2024.
 
The five-year, $42.5 million Dome exascale project will analyze data streams focused by a array of small dishes comprising a square kilometer (.6-by-.6 miles) worth of radio telescope area spread across an area 1,864 miles wide. As a result, the gigantic radio telescope will listen in on the faintest signals from the deepest parts of space where the oldest events occurred—notably the Big Bang from which the known universe originated. Along the way, it will also uncover the secrets of the mysterious dark matter that comprises 23 percent of the weight of the universe, but is invisible to conventional telescopes.

The gigantic Dome computing task being taken on by IBM's Center for Exascale Technology (Zurich) in cooperation with Astron—the Netherlands Institute for Radio Astronomy (Drenthe, the Netherlands)—will have a 12 year lead to construct the water-cooled three-dimensional (3-D) microchip technology necessary for a computing platform equivalent to millions of the world's fastest supercomputers running in parallel.

Besides 3-D computing cores, the Dome project will also develop optical data transport mechanisms based on nanophotonics and novel phase-change memory storage units. To keep the intense heat from the processors from melting down the computers, IBM will develop novel new cooling technologies that pump water through chips.

"We will leverage 3-D chip sets and water cooling to in order to have a very efficient way of processing the exabytes of data streaming in," said Martin Schmatz, a research scientist at IBM Zurich. "For storage we will also leverage novel new components like phase-change memories."

To realize the dream, IBM and Astron have also partnered with universities in Australia and South Africa to develop smarter analytics that are capable of automated machine learning that filters out noise and constructs ultra-detailed sky maps.


Previous
Next