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The decline of computers as a general purpose technology

Published: 22 February 2021 Publication History

Abstract

Technological and economic forces are now pushing computing away from being general purpose and toward specialization.

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References

[1]
Amazon Web Services: Elastic GPUs, 2017; https://aws.amazon.com/de/ec2/elastic-gpus/
[2]
Bloom, N., Jones, C., Van Reenen, J. and Webb, M. Are Ideas Getting Harder to Find? Cambridge, MA, 2017
[3]
Bresnahan, T.F. and Trajtenberg, M. General purpose technologies 'Engines of growth'? J. Econom. 65, 1 (Jan. 1995), 83--108
[4]
Byrne, D.M., Oliner, S.D. and Sichel, D.E. Is the information technology revolution Over? SSRN Electron. J. (2013), 20--36
[5]
Cavin, R.K., Lugli, P. and Zhirnov, V. V. Science and engineering beyond Moore's Law. In Proceedings of the IEEE 100, Special Centennial Issue (May 2012), 1720--1749
[6]
Dent, S. Major AMD chip supplier will no longer make next-gen chips, 2018; https://www.engadget.com/2018/08/28/global-foundries-stops-7-nanometer-chip-production/
[7]
Eastwood, G. How chip design is evolving in response to IoT development. Network World (2017); https://www.networkworld.com/article/3227786/internet-of-things/how-chip-design-is-evolving-in-response-to-iot-development.html
[8]
Economist. The future of computing---After Moore's Law (2016); https://www.economist.com/news/leaders/21694528-era-predictable-improvement-computer-hardware-ending-what-comes-next-future
[9]
Economist. The chips are down: The semiconductor industry and the power of globalization (2018); https://www.economist.com/briefing/2018/12/01/the-semiconductor-industry-and-the-power-of-globalisation.
[10]
ENIAC Report. Moore School of Electrical Engineering, 1946.
[11]
Feldmann, M. New GPU-accelerated supercomputers change the balance of power on the TOP500, 2018; https://www.top500.org/news/new-gpu-accelerated-supercomputers-change-the-balance-of-power-on-the-top500/
[12]
Gartner Group. Gartner Says Worldwide Semiconductor Revenue Grew 22.2 Percent in 2017. Samsung Takes Over No. 1 Position. Gartner. 2018; https://www.gartner.com/newsroom/id/3842666
[13]
Google Cloud. Google: Release Notes, 2018; https://cloud.google.com/tpu/docs/release-notes
[14]
Hemsoth, N. An Early Look at Baidu's Custom AI and Analytics Processor. The Next Platform; https://www.nextplatform.com/2017/08/22/first-look-baidus-custom-ai-analytics-processor/
[15]
Hennessy, J. and Patterson, D. Computer Architecture: A Quantitative Approach (6th ed.). Morgan Kaufmann Publishers, Cambridge, MA, 2019.
[16]
International Technology Roadmap for Semiconductors 2.0: Executive Report. International technology roadmap for semiconductors, 79, 2015; http://www.semiconductors.org/main/2015_international_technology_roadmap_for_semiconductors_itrs/
[17]
Jao, N. Taiwanese chip maker TSMC to build the world's first 3nm chip factory. Technode, 2018; https://technode.com/2018/12/20/taiwanese-chip-maker-tsmc-to-build-the-worlds-first-3nm-chip-factory/
[18]
Johnson, B., Tuan, S., Brady, W., Jim, W. and Jim, B. Gartner Predicts 2017: Semiconductor Technology in 2026.
[19]
Jouppi, N.P. et al. In-datacenter performance analysis of a tensor processing unit. In Proceedings of the 44th Annual Int. Symp. Comput. Archit. (2017), 1--12
[20]
Khan, H.N., Hounshell, D.A. and Fuchs, E.R.H. Science and research policy at the end of Moore's Law. Nat. Electron. 1, 1 (2018), 14--21
[21]
Khazraee, M., Zhang, L., Vega, L. and Taylor, M.B. Moonwalk? NRE optimization in ASIC clouds or accelerators will use old silicon. In Proceedings of ACM ASPLOS 2017, 1--16; https://doi.org/
[22]
Krzanich, B. Intel Corporation Presentation at Sanford C Berstein Strategic Decisions Conference, 2016.
[23]
Lapedus, M. Foundry Challenges in 2018. Semiconductor Engineering, 2017; https://semiengineering.com/foundry-challenges-in-2018/
[24]
Leiserson, C.E., Thompson, N., Emer, J., Kuszmaul, B.C., Lampson, B.W., Sanchez, D. and Schardl, T.B. There's plenty of room at the top: What will drive growth in computer performance after Moore's Law ends? Science (2020).
[25]
Martin, T.W. and Fitzgerald, D. Your love of your old smartphone is a problem for Apple and Samsung. WSJ (2018); https://www.wsj.com/articles/your-love-of-your-old-smartphone-is-a-problem-for-apple-and-samsung-1519822801
[26]
Mims, C. Huang's Law is the new Moore's Law, and explains why Nvidia wants arm. WSJ (2020); https://www.wsj.com/articles/huangs-law-is-the-new-moores-law-and-explains-why-nvidia-wants-arm-11600488001
[27]
NVIDIA Corporation. Tesla P100 Performance Guide. HPC and Deep Learning Applications, 2017.
[28]
Patton, G. Forging Intelligent Systems in the Digital Era. MTL Seminar, 2017; https://www-mtl.mit.edu/mtlseminar/garypatton.html#simple3
[29]
Pham, S. 2018. Who needs the US? Alibaba will make its own computer chips. CNN Business, 2018; https://edition.cnn.com/2018/10/01/tech/alibaba-chip-company/index.html
[30]
Prickett Morgan, T. Intel Takes First Steps To Universal Quantum Computing. Next Platform, 2017; https://www.nextplatform.com/2017/10/11/intel-takes-first-steps-universal-quantum-computing/
[31]
Putnam, A. et al. A reconfigurable fabric for accelerating large-scale datacenter services. Commun. ACM 59, 11 (Oct. 2016), 114--122
[32]
Santhanam, N., Wiseman, B., Campbell, H., Gold, A. and Javetski, B. McKinsey on Semiconductors, 2015.
[33]
Shalf, J.M. and Leland, R. Computing beyond Moore's Law. Computer 48, 12 (Dec. 2015), 14--23
[34]
Shao, Y.S., Reagen, B., Wei, G.Y., and Brooks, D. Aladdin: A pre-RTL, power-performance accelerator simulator enabling large design space exploration of customized architectures. In Proceedings of the Int. Symp. Comput. Archit. (2014), 97--108
[35]
Semiconductor Industry Association: 2017 Factbook; http://go.semiconductors.org/2017-sia-factbook-0-0-0
[36]
Smith, S.J. Intel: Strategy Overview, 2017
[37]
Top500. The Green500 List (June 2019); https://www.top500.org/green500/lists/2019/06/
[38]
Worldometers. Computers sold in the world this year, 2018; http://www.worldometers.info/computers/

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Published In

cover image Communications of the ACM
Communications of the ACM  Volume 64, Issue 3
March 2021
115 pages
ISSN:0001-0782
EISSN:1557-7317
DOI:10.1145/3452024
Issue’s Table of Contents
This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 February 2021
Published in CACM Volume 64, Issue 3

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