Communications of the ACM
Could Analog Computing Accelerate Complex Computer Simulations?
The U.S. Defense Advanced Research Projects Agency has issued a request for information on methods for using analog approaches to speed up scientific computing.
Credit: CoreyPadveen.com
The U.S. Defense Advanced Research Projects Agency (DARPA) announced a request for information (RFI) on methods for using analog approaches to speed up computation of the mathematics that characterize scientific computing.
"The standard [digital] computer cluster equipped with multiple central processing units [CPUs], each programmed to tackle a particular piece of a problem, is just not designed to solve the kinds of equations at the core of large-scale simulations, such as those describing complex fluid dynamics and plasmas," says DARPA program manager Vincent Tang.
These equations, or partial differential equations, describe fundamental physical principles such as motion, diffusion, and equilibrium. However, they involve continuous rates of change over a large range of physical parameters relating to the problems of interest, making then unsuitable to being broken up and solved in discrete pieces by individual CPUs.
Tang says novel computational substrates could exceed the performance of modern CPUs for certain specialized problems, if they can be scaled and integrated into modern computer architectures.
The RFI seeks new processing paradigms with the potential to overcome current barriers in computing performance. "In general, we're interested in information on all approaches, analog, digital, or hybrid ones, that have the potential to revolutionize how we perform scientific simulations," he says.
From KurzweilAI.net
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