Build your own supercomputer

The term “supercomputer” is a loose one. There’s no official definition, so there’s nothing preventing you from applying the term to your desktop PC, laptop or digital watch.

Broadly, though, it refers to a computer that’s much more powerful than the typical hardware of its period.

The first supercomputer is often said to be the CDC 6600, designed in the early 1960s by Seymour Cray (whose name would become synonymous with supercomputing). It could perform calculations at a rate of around one megaflops – that is, one million floating-point arithmetical operations per second; roughly five times the performance of a contemporary mainframe such as the IBM 7090.

Today, the term might refer to a system such as the Fujitsu K computer, capable of more than ten petaflops – a staggering ten-billionfold increase over the original Cray. The two aren’t perfectly comparable since the two systems performed quite different tasks, but it’s clear we’re dealing with vast amounts of power.

Supercomputing applications

It might not be immediately obvious what anybody might need with such incredible computational power, but there are a number of real-world tasks that will devour all the processing resources you can throw at them.

It might not be immediately obvious what anybody might need with such incredible computational power, but there are a number of real-world tasks that will devour all the processing resources you can throw at them

In scientific research, supercomputers can be used to test fluid dynamic or aerodynamic models without the need to build expensive prototypes. At CERN, supercomputers perform simulated subatomic experiments.

Seismologists use supercomputer resources to model the effects of earthquakes, and meteorologists can rapidly analyse large quantities of sensor data to predict how weather systems will develop.

Supercomputing is at the forefront of new technologies, too. Creating a computer interface that responds to natural language, for example, is an extremely challenging task, owing to the immense variety of sounds, situations and nuances that must be understood; the more horsepower that can be thrown at the problem, the better it will be.

Looking further ahead, supercomputing could even deliver the holy grail of artificial intelligence. Back in 1997, IBM’s Deep Blue supercomputer notoriously defeated grandmaster Garry Kasparov at chess.

Its Blue Gene/P supercomputer, unveiled in 2007, has been used to simulate a neural network of 1.6 billion neurons, representing around 1% of the complexity of the human brain.

And last year, IBM’s Watson computer appeared as a contestant on US game show Jeopardy!, defeating two former champions to walk away – well, to be wheeled away – with a million-dollar prize.

A supercomputer at home

Few of us run seismology labs, or develop artificial intelligence systems. However, there are domestic roles for supercomputing, too. If you’re a budding film-maker, you’ll know that creating sophisticated cinematic effects involves much intensive computation. The more power you have on hand, the more quickly you can try things out and see results.

With enough grunt, you could recreate the photorealistic animations of Michael Bay’s Transformers movies, or the fantastically detailed world of Wall-E – but even for a dedicated studio such as Pixar, each frame of an animated movie can take around 90 minutes to render.

The precise figure varies from frame to frame, depending on its complexity, and the computing resources available. Many scenes are rendered simultaneously – otherwise a film such as Toy Story 3 would take decades to render.

With a high-performance computer, you can also play a big part in distributed projects such as [email protected] and [email protected] These projects let you use your computer to analyse raw data for worthy causes; in the case of [email protected], you’ll be analysing radio telescope data for possible evidence of extraterrestrial life.

The [email protected] project uses volunteer computing power to conduct simulated experiments that could lead to treatments for diseases such as Alzheimer’s and Parkinson’s (the project takes its name from the way proteins “fold” into shapes that cause various behaviours within the human body).

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