A Million Trillion Flops. More Than Ben Affleck
Sandia is a US Department of Energy research and development laboratory run by Lockheed Martin. They're presently gearing up to add some zeros to amount of calculations a supercomputer can perform. Sandia developed the first teraflop (one trillion calculations a second) computer a decade ago. They've decided to take it up more than a notch. Behold the exaflop: a million trillion flops.
“An exascale computer is essential to perform more accurate simulations that, in turn, support solutions for emerging science and engineering challenges in national defense, energy assurance, advanced materials, climate, and medicine,” says James Peery, director of computation, computers and math.
The institute is funded in FY08 by congressional mandate at $7.4 million. It is supported by the National Nuclear Security Administration and the Department of Energy’s Office of Science. Sandia is an NNSA laboratory.
One aim, Dosanjh says, is to reduce or eliminate the growing mismatch between data movement and processing speeds.
Sandia researchers referred to the problems inherent in simply increasing clock speed to achieve this greater capacity, and the need to concurrently develop parallel operating systems that use all the numerous cores on a chip simultaneously to drive big increases in computing capacity. I don't care how powerful they make it. I just know that I'm still going to cringe when I accidentally click on a PDF file on my Google results.
“An exascale computer is essential to perform more accurate simulations that, in turn, support solutions for emerging science and engineering challenges in national defense, energy assurance, advanced materials, climate, and medicine,” says James Peery, director of computation, computers and math.
The institute is funded in FY08 by congressional mandate at $7.4 million. It is supported by the National Nuclear Security Administration and the Department of Energy’s Office of Science. Sandia is an NNSA laboratory.
One aim, Dosanjh says, is to reduce or eliminate the growing mismatch between data movement and processing speeds.
Sandia researchers referred to the problems inherent in simply increasing clock speed to achieve this greater capacity, and the need to concurrently develop parallel operating systems that use all the numerous cores on a chip simultaneously to drive big increases in computing capacity. I don't care how powerful they make it. I just know that I'm still going to cringe when I accidentally click on a PDF file on my Google results.
