The future of computing beyond Moore’s Law
By John M. Shalf. Philosophical Transactions of the Royal Society A, 2020
493 citations recorded by the source corpus.
Moore’s Law is a techno-economic model that has enabled the information technology industry to double the performance and functionality of digital electronics roughly every 2 years within a fixed cost, power and area. Advances in silicon lithography have enabled this exponential miniaturization of electronics, but, as transistors reach atomic scale and fabrication costs continue to rise, the classical technological driver that has underpinned Moore’s Law for 50 years is failing and is anticipated to flatten by 2025. This article provides an updated view of what a post-exascale system will look like and the challenges ahead, based on our most recent understanding of technology roadmaps. It also discusses the tapering of historical improvements, and how it affects options available to continue scaling of successors to the first exascale machine. Lastly, this article covers the many different opportunities and strategies available to continue computing performance improvements in the absence of historical technology drivers. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems and Management
View Paper: https://www.semanticscholar.org/paper/9abb8d6603707a5f54fdd5ec9173e6717d001935
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Citations in the corpus
- Physics-informed machine learning: case studies for weather and climate modelling (2021, background): “In a nutshell, three key forces have contributed to the unprecedented success of ML and DL [3]: (i) access to vast quantities of data; (ii) advances in computational algorithms; and (iii) an exponential increase in computational horsepower in accordance with Moore’s Law [4,5].”
- The hardware lottery (2020, background): “However, even investment of this magnitude may still be woe-fully inadequate, as hardware based on new materials requires long lead times of 10 - 20 years and public investment is currently far below industry levels of R&D (Shalf, 2020).”
- Usage impact on data center electricity needs: A system dynamic forecasting model (2021, background): “Moore ’ s law –which predicts a 25% annual energy decline per processing unit (or as often said a performance doubling each 2 years)– is expected to stop having an influence by 2021 and 2023 [2].”