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Zettascale computing

From Wikipedia, the free encyclopedia

Zettascale computing refers to computing systems capable of calculating at least "1021 IEEE 754 Double Precision (64-bit) operations (multiplications and/or additions) per second (zettaFLOPS)".[1] It is a measure of supercomputer performance, and as of July 2022 is a hypothetical performance barrier.[2] A zettascale computer system could generate more single floating point data in one second than was stored by the total digital means on Earth in the first quarter of 2011.[citation needed]

Definitions

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Floating point operations per second (FLOPS) are one measure of computer performance. FLOPS can be recorded in different measures of precision, however the standard measure (used by the TOP500 supercomputer list) uses 64 bit (double-precision floating-point format) operations per second using the High Performance LINPACK (HPLinpack) benchmark.[3][4]

Forecasts

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In 2018, Chinese scientists predicted that the first zettascale system will be assembled in 2035.[5] This forecast looks plausible from a historical point of view as it took some 12 years to progress from the terascale machines (1012) to petascale systems (1015) and then 14 more years to move to exascale computers (1018).[5]

Scientists forecast that the zettascale systems are likely to be data-centric; this proposition means that the system components will move to the data, not vice versa, as the data volumes in the future are anticipated to be so large that moving data will be too expensive. It is also forecasted that zettascale systems are expected to be decentralized—because such a model can be the shortest route to achieving zettascale performance, with millions of less powerful components linked and working together to form a collective hypercomputer that is more powerful than any single machine.[5] Such decentralized systems may be designed to mimick complex biologic systems, and the next cybernetic paradigm may be based on liquid cybernetic systems with embodied intelligence solutions.[6][clarification needed]

Potential configuration

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China’s National University of Defense Technology propose the following metrics:[7]

  • Power consumption: 100 MW
  • Power efficiency: 10 teraflops/watt
  • Peak performance per node: 10 petaflops
  • Communication bandwidth between nodes: 1.6 terabits/second
  • I/O bandwidth: 10 to 100 petabytes/second
  • Storage capacity: 1.0 zettabyte
  • Floor space: 1000 square meters

Problems

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As Moore's law nears its natural limits, supercomputing will face serious physical problems in moving from exascale to zettascale systems, making the decade after 2020 a vital period to develop key high-performance computing techniques.[8] Many forecasters, including Gordon Moore himself,[9] expect Moore's law to end by around 2025.[10][11] Another challenge for reaching zettascale performance can be enormous energy consumption.[12][13]

Applications

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  • Zettascale computers will be able to accurately forecast global weather for 2 weeks in the future.[14]
  • Zettascale calculations will also be able to significantly reduce the time required for astrophysical simulations of such rare phenomena as black holes, neutron star mergers, and supernovae. For example, the calculating of a 3D model of shock wave instability from a collapsing supernova core, which takes 1 million hours on petaflops computers and 1000 hours on exaflops machines, can be done in just one hour on zettaflops systems.[15]
  • Zettascale or yottascale systems might be able to accurately model the whole human brain.[16]

See also

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References

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  1. ^ "What is zettaflops? - Definition from WhatIs.com". WhatIs.com. Retrieved 24 August 2021.
  2. ^ Feldman, Michael (11 December 2018). "Supercomputing Is Heading Toward an Existential Crisis". top500.org. Retrieved 24 August 2021.
  3. ^ "FREQUENTLY ASKED QUESTIONS". www.top500.org. Retrieved 23 June 2020.
  4. ^ Kogge, Peter, ed. (1 May 2008). ExaScale Computing Study: Technology Challenges in Achieving Exascale Systems (PDF). United States Government. Retrieved 28 September 2008.
  5. ^ a b c August 2020, Joel Khalili 29 (29 August 2020). "I confess, I'm scared of the next generation of supercomputers". TechRadar. Retrieved 24 August 2021.{{cite web}}: CS1 maint: numeric names: authors list (link)
  6. ^ Chiolerio, Alessandro; Draper, Thomas C.; Jost, Carsten; Adamatzky, Andrew (2019). "Electrical Properties of Solvated Tectomers: Toward Zettascale Computing". Advanced Electronic Materials. 5 (12): 1900202. doi:10.1002/aelm.201900202. S2CID 204646269.
  7. ^ "Will 1000 ExaFlop Supercomputers Come from Brute Force Scaling or New Technology? | NextBigFuture.com". nextbigfuture.com. Retrieved 6 October 2021.
  8. ^ Liao, Xiang-ke; Lu, Kai; Yang, Can-qun; Li, Jin-wen; Yuan, Yuan; Lai, Ming-che; Huang, Li-bo; Lu, Ping-jing; Fang, Jian-bin; Ren, Jing; Shen, Jie (1 October 2018). "Moving from exascale to zettascale computing: challenges and techniques". Frontiers of Information Technology & Electronic Engineering. 19 (10): 1236–1244. doi:10.1631/FITEE.1800494. ISSN 2095-9230. S2CID 53819223. Retrieved 24 August 2021.
  9. ^ Cross, Tim. "After Moore's Law". The Economist Technology Quarterly. Retrieved 13 March 2016. chart: "Faith no Moore" Selected predictions for the end of Moore's law
  10. ^ Kumar, Suhas (2012). "Fundamental Limits to Moore's Law". arXiv:1511.05956 [cond-mat.mes-hall].
  11. ^ McBride, Stephen (23 April 2019). "These 3 Computing Technologies Will Beat Moore's Law". Forbes. Retrieved 24 August 2021.
  12. ^ Morgan, James (18 October 2013). "IBM unveils computer fed by 'electronic blood'". BBC News. Retrieved 4 October 2021.
  13. ^ Hayes, Brian (22 July 2014). "Built for speed: Designing exascale computers". Harvard University. Retrieved 4 October 2021.
  14. ^ DeBenedictis, Erik P. (2005). "Reversible logic for supercomputing". Proceedings of the 2nd conference on Computing frontiers. ACM Press. pp. 391–402. ISBN 1-59593-019-1.
  15. ^ "Суперкомпьютеры достигают производительности в зеттафлопс | "Будущее сейчас"" (in Russian). futurenow.ru. Retrieved 29 September 2021.
  16. ^ Kirkpatrick, Kay (2019). "BIO LOGIC: Biological Computation" (PDF). University of Illinois.
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