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Design challenges of technology scaling
Abstract
Scaling advanced CMOS technology to the next generation improves performance, increases transistor density, and reduces power consumption. Technology scaling typically has three main goals: 1) reduce gate delay by 30%, resulting in an increase in operating frequency of about 43%; 2) double transistor density; and 3) reduce energy per transition by about 65%, saving 50% of power (at a 43% increase in frequency). These are not ad hoc goals; rather, they follow scaling theory. This article looks closely at past trends in technology scaling and how well microprocessor technology and products have met these goals. It also projects the challenges that lie ahead if these trends continue. This analysis uses data from various Intel microprocessors; however, this study is equally applicable to other types of logic designs. Is process technology meeting the goals predicted by scaling theory? An analysis of microprocessor performance, transistor density, and power trends through successive technology generations helps identify potential limiters of scaling, performance, and integration.
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Cited by
(2006) · Cited by 1,979
How much energy is needed to run a wireless network?
Auer, G., Giannini, V., Desset, C., Godor, I., Skillermark, P., Olsson, M., Imran, M., Sabella, D., Gonzalez, M., Blume, O., et al. (2011) · IEEE Wireless Communications · doi:10.1109/mwc.2011.6056691 · Cited by 1,539
Borkar, S. (2005) · IEEE Micro · doi:10.1109/mm.2005.110 · Cited by 1,320
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Metadata
- Authors
- Borkar, S.
- Venue
- IEEE Micro
- Published
- 1999
- Volume
- 19
- Issue
- 4
- Pages
- 23-29
- ISSN
- 0272-1732 (ISSN-L)
- OpenAlex
- W2125263803
- Cited by
- 1,164
- References
- 0
- FWCI
- 32.93
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.