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Cloud Computing's Killer App: Gaming

AMD's proposed online supercomputer will handle gaming graphics so your cellphone won't have to

3 min read

In recognition of the huge importance of graphics and gaming to the future of computing, Advanced Micro Devices (AMD), of Sunnyvale, Calif., is building the fastest commercial supercomputer in the world and selling its use to makers of online games. When it’s ready, in the second half of 2009, it will manage a thousand million million floating-point operations per second—a petaflop. That will put it on a par with Roadrunner, the U.S. Department of Energy’s most powerful machine.

The idea is to compute a game’s graphics, compress them, and send them out over the Internet so that online gamers can run the results on platforms, such as cellphones, that are too computationally puny to render the graphics on their own. Game makers would write their software for the supercomputer—rather than for a PC, smart phone, or other platform—and then rent computer time and bandwidth on AMD’s machine. It’s a particularly striking example of the shift in the balance of power away from the platform and into the network, or cloud—hence the computer’s name, the Fusion Render Cloud.

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The Future of Deep Learning Is Photonic

Computing with light could slash the energy needs of neural networks

10 min read

This computer rendering depicts the pattern on a photonic chip that the author and his colleagues have devised for performing neural-network calculations using light.

Alexander Sludds
DarkBlue1

Think of the many tasks to which computers are being applied that in the not-so-distant past required human intuition. Computers routinely identify objects in images, transcribe speech, translate between languages, diagnose medical conditions, play complex games, and drive cars.

The technique that has empowered these stunning developments is called deep learning, a term that refers to mathematical models known as artificial neural networks. Deep learning is a subfield of machine learning, a branch of computer science based on fitting complex models to data.

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