Physicists and computer scientists have recently expanded the modern theory of the thermodynamics of computation.
By combining approaches from statistical physics and computer science , the researchers introduce mathematical equations that reveal the minimum and maximum predicted energy cost of computational processes that depend on randomness, which is a powerful tool in modern computers.
In particular, the framework offers insights into how to compute energy-cost bounds on computational processes with an unpredictable finish. For example: A coin-flipping simulator may be instructed to stop flipping once it achieves 10 heads. In biology, a cell may stop producing a protein once it elicits a certain reaction from another cell. The"stopping times" of these processes, or the time required to achieve the goal for the first time, can vary from trial to trial.
In recent studies that laid the groundwork for this new paper, Wolpert and colleagues introduced the idea of a"mismatch cost," or a measure of how much the cost of a computation exceeds Landauer's bound. Proposed in 1961 by physicist Rolf Landauer, this limit defines the minimum amount of heat required to change information in a computer. Knowing the mismatch cost, Wolpert says, could inform strategies for reducing the overall energy cost of a system.
Taken together, their research point to a new avenue for finding the lowest energy needed for computation in any system, no matter how it's implemented."It's exposing a vast new set of issues," Wolpert says.
Physics Energy Technology Solar Energy Computer Science Computer Modeling Computers And Internet Distributed Computing
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