Why We Can Expect Ever More Amazing Mobile Computing Devices in the Years Ahead
Information technology (IT) has captured the popular imagination, in part because of the tangible benefits IT brings, but also because the underlying technological trends proceed at easily measurable, remarkably predictable, and unusually rapid rates. The number of transistors on a chip has doubled more or less every two years for decades, a trend that is popularly (but often imprecisely) encapsulated as “Moore’s Law.”
This talk will explore the relationship between the performance of computers and the electricity needed to deliver that performance. Computations per kWh grew about as fast as performance for desktop computers starting in 1981, doubling every 1.5 years, a pace of change in computational efficiency comparable to that from 1946 to the present. Computations per kWh grew even more rapidly during the vacuum tube computing era and during the transition from tubes to transistors but more slowly during the era of discrete transistors. As expected, the transition from tubes to transistors shows a large jump in computations per kWh.
In 1985, the physicist Richard Feynman identified a factor of one hundred billion possible theoretical improvement in the electricity used per computation. Since that time computations per kWh have increased by less than five orders of magnitude, leaving significant headroom for continued improvements. The main trend driving towards increased performance and reduced costs, namely smaller transistor size, also tends to reduce power use, which explains why the industry has been able to improve computational performance and electrical efficiency at similar rates. If these trends continue (and we have every reason to believe they will for at least the next five to ten years), this research points towards continuing rapid reductions in the size and power use of battery-powered mobile computers, allowing further rapid progress in mobile sensors, computing, and controls.
The paper documenting the work to be summarized in this talk is Koomey, Jonathan G., Stephen Berard, Marla Sanchez, and Henry Wong. 2010. “Implications of Historical Trends in The Electrical Efficiency of Computing.” In Press at the IEEE Annals of the History of Computing. March.
Jonathan Koomey http://www.koomey.com is a Consulting Professor at Stanford University, worked for more than two decades at Lawrence Berkeley National Laboratory, and has been a visiting professor at Yale University (Fall 2009) and Stanford University (2004-5 and Fall 2008). Dr. Koomey holds M.S. and Ph.D. degrees from the Energy and Resources Group at UC Berkeley, and an A.B. in History of Science from Harvard University. He is the author or coauthor of eight books and more than 150 articles and reports, and is one of the leading international experts on the economics of reducing greenhouse gas emissions and the effects of information technology on resource use. His latest solo book is the 2nd edition of Turning Numbers into Knowledge: Mastering the Art of Problem Solving, with more than 30,000 copies in print in English, Chinese, Italian, and (soon) Korean. http:/www.analyticspress.com.
- Jonathan Koomey
- Stanford University