Excerpt

Currently about 5% of all energy consumption in the US goes to running computers (Desroches et al., n.d.), 1 and similar figures are reported in Europe (Avgerinou, Bertoldi, and Castellazzi 2017). This is a huge monetary cost to the US economy, and the associated burning of carbon is a huge cost to the worldwide environment. Such costs of computation also arise at the much smaller scale of individual computers. For example, a large fraction of the lifetime budget of a modern high-performance computing center goes to pay its energy bill.

Despite these energetic costs of computing, the amount of computation will continue to grow at a prodigious rate. Accordingly, improving the energy efficiency of current and near-future computers is a crucial challenge facing humanity. Indeed, the benefits of improved energy efficiency would extend beyond reducing economic and environmental costs. In particular, reducing the rate of heat production is crucial for the development of next-generation high-performance computers, as dumping heat (i.e., cooling the components) is a major engineering challenge.

These issues do not arise only in artificial, silicon-based digital computers. There are many naturally occurring computers, and they, too, require huge amounts of energy. To give a rather pointed example, the human brain is a computer. This particular computer uses some 10–20% of all the calories that a human consumes. Ultimately, the cost of this computer, which uses energy that could be applied towards reproduction, must be balanced by the gains provided by the computations it performs, such as a greater ability to find food and avoid becoming prey. This implies that natural selection acts on the overall combined energetic and computational efficiency of the brain. Thus, analyzing the evolutionary biology of the thermodynamic costs of biological intelligence should be an important aspect of future research.

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