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article · Computing in Science & Engineering · 2011

Extreme Data-Intensive Scientific Computing

Alexander S. Szalay

Cited by 51Abstract and details only

Abstract

Scientific computing increasingly involves massive data; in astronomy, observations and numerical simulations are on the verge of generating petabytes. This new, data-centric computing requires a new look at computing architectures and strategies. Using Amdahl's law to characterize architectures and workloads, it's possible to use existing commodity parts to build systems that approach an ideal Amdahl machine.

Cite this paper

APA 7

Szalay, A. S. (2011). Extreme Data-Intensive Scientific Computing. Computing in Science & Engineering, 13(6), 34–41. https://doi.org/10.1109/mcse.2011.74

MLA 9

Szalay, Alexander S. “Extreme Data-Intensive Scientific Computing.” Computing in Science & Engineering, vol. 13, no. 6, 2011, pp. 34–41, https://doi.org/10.1109/mcse.2011.74.

Chicago

Szalay, Alexander S. 2011. “Extreme Data-Intensive Scientific Computing.” Computing in Science & Engineering 13 (6): 34–41. https://doi.org/10.1109/mcse.2011.74.

Harvard

Szalay, A.S. (2011) ‘Extreme Data-Intensive Scientific Computing’, Computing in Science & Engineering, 13(6), pp. 34–41. Available at: https://doi.org/10.1109/mcse.2011.74.

BibTeX
@article{szalay2011extreme,
  title = {{Extreme Data-Intensive Scientific Computing}},
  author = {Szalay, Alexander S.},
  journal = {Computing in Science & Engineering},
  volume = {13},
  number = {6},
  pages = {34--41},
  year = {2011},
  doi = {10.1109/mcse.2011.74}
}

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