From photons to big-data applications: terminating terabits
hilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Royal Society Publishing
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Zilberman, N., Moore, A., & Crowcroft, J. (2016). From photons to big-data applications: terminating terabits. hilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374 (2062. 20140445)https://doi.org/10.1098/rsta.2014.0445
Computer architectures have entered a watershed as the quantity of network data generated by user applications exceeds the data-processing capacity of any individual computer end-system. It will become impossible to scale existing computer systems while a gap grows between the quantity of networked data and the capacity for per system data processing. Despite this, the growth in demand in both task variety and task complexity continues unabated. Networked computer systems provide a fertile environment in which new applications develop. As networked computer systems become akin to infrastructure, any limitation upon the growth in capacity and capabilities becomes an important constraint of concern to all computer users. Considering a networked computer system capable of processing terabits per second, as a benchmark for scalability, we critique the state of the art in commodity computing, and propose a wholesale reconsideration in the design of computer architectures and their attendant ecosystem. Our proposal seeks to reduce costs, save power and increase performance in a multi-scale approach that has potential application from nanoscale to data-centre-scale computers.
computer architecture, interconnect, networking, performance guarantees
This work was supported by the UK Engineering and Physical Sciences Research Council INTERNET Project EP/H040536/1. This work was supported by the Defense Advanced Research Projects Agency and the Air Force Research Laboratory, under contract FA8750-11-C-0249.
EPSRC (via University of Leeds) (RGELEC476868)
European Commission FP7 Marie Curie Innovative Training Networks (ITN) (607764)
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External DOI: https://doi.org/10.1098/rsta.2014.0445
This record's URL: https://www.repository.cam.ac.uk/handle/1810/252999
Attribution 2.0 UK: England & Wales
Licence URL: http://creativecommons.org/licenses/by/2.0/uk/