The Anatomy of a Supercomputer
Today, you can hold the equivalent of a decades-ago supercomputer in the palm of your hand. Thirty years ago, the ability to perform 1 billion floating-point calculations per second would have set you back a cool $15 million. Today, what sits in your pocket next to the car keys can best that number by an order of magnitude or more…
Today’s computers owe their success to early breakthroughs in semiconductor technology that allowed circuits to store data compactly in the form of bits. These bits of data, stored as tiny electrical charges, are like tiny switches. They can be either on or off. These two states correspond to “1” or “0,” which allows computer designers to build logic circuits using binary math.
Everything we do with computers — from reading this article on a mobile device to solving the world’s toughest problems on supercomputers — is ultimately broken down to a series of 1 and 0 bits in the innards of a computer.
A modern computer, even a relatively modest one, is built out of billions of these tiny switches.
Thanks to increasing miniaturization, we can cram more and more of those little bit-holding electronic elements into a circuit, and we can do it cheaper as well. This steady improvement, first described by Intel co-founder Gordon Moore, has driven up performance and driven down costs.
Just as early breakthroughs in traditional computing technology enabled today’s generation of digital computers, new breakthroughs in quantum computing will change the game again.
Quantum computers, which use quantum mechanics to perform computations, use quantum bits to store data, rather than bits. Also called qubits, these units of data storage can assume more than two states. In fact, unlike the tiny switches present in binary electronic computers, a qubit can assume a vast number of different states.
A practical quantum computer would enable computing power beyond anything we’ve ever seen. In theory, a quantum computer composed out of only a few hundred working qubits could contain more data than there are atoms in the universe. A binary bit computer, even with trillions of traditional bits, wouldn’t stand a chance.
It strains the imagination to consider what kind of computing applications quantum computing could enable. At the very least, difficult computational problems that consume vast computing resources in scientific research could become far more tractable. More-accurate weather forecasting, superior modeling for engineering applications and better simulations of how the body functions would prove transformational in their respective fields.
If we learned how to make quantum computing inexpensive and accessible to the average person, super-secure communications and true natural language recognition would be possible. Quantum circuits could perhaps enable artificially intelligent machines that would relieve humans of the drudgery and danger of many different kinds of work.
Recently, a small Canadian company is moving the quantum ball forward in a big way. D-Wave Systems Canada, specializes in making quantum computing a reality. It has, in fact, already sold commercial systems to defense contractor Lockheed Martin as well as Google.
The company’s technology is based on superconducting adiabatic quantum processors. Quantum mechanics allows electrical current in a superconducting loop to be both “1” and “0” at the same time.
Without getting into too many details, this technology allows D-Wave to get around existing technological limitations that come from trying to use individual subatomic particles to perform computational functions. D-Wave’s qubit elements can be manufactured at scales current technology can handle.
Earlier this year, a D-Wave quantum computer composed of 84 qubits was used to solve an extraordinarily difficult math problem: the calculation of a Ramsey number. The 84-qubit quantum computer used 28 qubits for actual computation and the other 56 for error corrections.
Ramsey numbers give the solution to what is known as the “party problem.” The problem sounds simple enough: How many people do you need to invite to a party so that so that a defined group of them (m) know each other but another defined group (n) do not? The number is usually expressed as R(m,n).
Although the problem sounds simple, it is actually incredibly difficult to calculate as m and n scale up. Hungarian mathematician Paul Erdős once famously said that if an alien force threatened us with invasion unless we provided the solution to R(5,5), we should put all of our computers and mathematicians to work on it immediately. If, however, they asked for R(6,6), we should prepare for war. If we used conventional computers to solve the problem through brute force calculation, the amount of years needed would start with a 1 and be followed by 250 zeros.
D-Wave has had plenty of naysayers over the years claim it doesn’t have a working quantum computer.
So how well did D-Wave’s quantum computer do?
The 84-qubit computer solved the Ramsey number problem for R(8,2) in 270 milliseconds with only 24 qubits actually working on the problem.
These impressive results are only the beginning of the quantum computing revolution. This will lead to computers that will be smaller and faster than you can imagine. Pioneers such as D-Wave (and their earliest investors) stand to share the biggest rewards…
Ad lucrum per scientia (toward wealth through science),
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