We've covered what super computers are here in this video, and they are indeed
super. The fastest machines today are in the realm of petascale computing, that's
more than a quadrillion computing operations per second. The most powerful
computer in the world today is Summit, the supercomputer at Oak Ridge National
Lab. It's followed closely by Lawrence Livermore's Sierra supercomputer, but even
today's most powerful high-performance machines can't keep up with the demands
of the increasingly complex simulations required for national security, precision
medicine, climate research, and a host of other areas of basic science. So, what's
next ? Some computing experts have called improving computing performance on this
huge scale the 'space race of this century' because after petascale
computing, comes exascale computing. If petascale is a quadrillion calculations
per second, exascale is a quintillion operations per second. That's 18 zeroes
in one second. 10 to the 18th. And by the way—that's why Axascale Day is on
October 18th! Get it? It's a small word for an almost unimaginably big number. If
we went back in time a quintillion seconds? That's about 32 billion years
ago...18 billion years before the Big Bang. A quintillion is about the number of
neurons in ten million human brains. And if you somehow linked the top 100
fastest and most powerful supercomputers in the world right now and had them all
work together on a single problem, you still wouldn't reach the computing power
of one exascale system. If we look back at the progress we've made in improving
computing power, we've made these strides because we've been able to pack more and
more computing power into smaller and smaller spaces. That improvement in power
has been holding steady for many years, but we're starting to see it slow down.
We can't get the transistors any smaller, and plus moving data around within a
computing system that large takes so much energy. Huge leaps in computing also
require leaps in the accompanying infrastructure. Interdisciplinary innovation has
resulted in improvements to the architecture, data storage and management,
and the kinds of software that can run on these machines. This and much more is
what has made exascale computing a reality. The nation's first exascale
system, Aurora, is slated for arrival at Argonne National Lab in 2021, followed
later that year by Frontier at Oak Ridge National Lab, and El Capitan at Lawrence
Livermore in 2022, projected to perform at more than 1.5 exaflops.
That's one-and-a-half quintillion operations per second. But why do we need
this huge leap in computing power? At a national lab like Lawrence Livermore,
scientists rely on computer modeling and simulations to solve problems that are
way beyond the scope of any human. And see, the universe is in 3D. And the
ability to incorporate additional physics into 3D simulations and perform
them regularly means that the information scientists get from these
models will be closer than ever before to what happens in the real world. El
Capitan will allow scientists and physicists to perform larger and higher-
resolution 3D simulations than ever before, and fast. Simulations that might
take a week to perform on Sierra— Livermore's existing petascale computer—
could be completed in a single workday on El Capitan. El Capitan's primary mission
will be supporting America's national security missions, ensuring the safety,
security, and effectiveness of the nation's nuclear stockpile in the
absence of underground testing. Across the Department of Energy, exascale
computing will help scientists answer some of the biggest and most fundamental
questions humanity has. It will allow for faster, more detailed models in areas of
basic science such as predicting the effects of climate change, simulating how
drug molecules interact, with the body in order to create more effective
medications, optimizing designs for 3D printing studying, earthquakes, or how the
100 billion neurons the human brain connect and function.
Throughout history we've pushed the boundaries of humanity's ability to
understand and ask questions of our universe, and exascale computing is
simply the next step in better, faster science. And what's next,
beyond exascale computing, beyond the boundary of Moore's Law, into the realm
of fields like quantum computing? Well, we can only imagine.