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article · Electronic Imaging · 2016

Making Advanced Scientific Algorithms and Big Scientific Data Management More Accessible

Singanallur Venkatakrishnan, K. Aditya Mohan, K. Beattie, Joaquin Correa, Eli Dart, Jack Deslippe, Alexander Hexemer, Harinarayan Krishnan, Alastair A. MacDowell, Stefano Marchesini, Simon Patton, Talita Perciano, James A. Sethian, Rune Stromsness, Brian L. Tierney, C. E. Tull, Daniela Ushizima, Dilworth Y. Parkinson

Cited by 9Open access

Abstract

Synchrotrons such as the Advanced Light Source (ALS) at Lawrence Berkeley National Laboratory are user facilities - they are sources of extremely bright X-ray beams, and scientists come from all over the world to perform experiments that require these beams. As the complexity of experiments has increased, and the size and rates of data sets has exploded, managing, analyzing and presenting the data collected at synchrotrons has been an increasing challenge. The ALS has partnered with high performance computing, fast networking, and applied mathematics groups to create a“super-facility”, giving users simultaneous access to the experimental, computational, and algorithmic resources to overcome this challenge. This combination forms an efficient closed loop, where data despite its high rate and volume is transferred and processed, in many cases immediately and automatically, on appropriate compute resources, and results are extracted, visualized, and presented to users or to the experimental control system, both to provide immediate insight and to guide decisions about subsequent experiments during beam-time. In this paper, We will present work done on advanced tomographic reconstruction algorithms to support users of the 3D micron-scale imaging instrument (Beamline 8.3.2, hard X-ray micro-tomography).

Cite this paper

APA 7

Venkatakrishnan, S., Mohan, K. A., Beattie, K., Correa, J., Dart, E., Deslippe, J., Hexemer, A., Krishnan, H., MacDowell, A. A., Marchesini, S., Patton, S., Perciano, T., Sethian, J. A., Stromsness, R., Tierney, B. L., Tull, C. E., Ushizima, D., & Parkinson, D. Y. (2016). Making Advanced Scientific Algorithms and Big Scientific Data Management More Accessible. Electronic Imaging, 28(19), 1–7. https://doi.org/10.2352/issn.2470-1173.2016.19.coimg-155

MLA 9

Venkatakrishnan, Singanallur, et al. “Making Advanced Scientific Algorithms and Big Scientific Data Management More Accessible.” Electronic Imaging, vol. 28, no. 19, 2016, pp. 1–7, https://doi.org/10.2352/issn.2470-1173.2016.19.coimg-155.

Chicago

Venkatakrishnan, Singanallur, K. Aditya Mohan, K. Beattie, Joaquin Correa, Eli Dart, Jack Deslippe, Alexander Hexemer, et al. 2016. “Making Advanced Scientific Algorithms and Big Scientific Data Management More Accessible.” Electronic Imaging 28 (19): 1–7. https://doi.org/10.2352/issn.2470-1173.2016.19.coimg-155.

Harvard

Venkatakrishnan, S. et al. (2016) ‘Making Advanced Scientific Algorithms and Big Scientific Data Management More Accessible’, Electronic Imaging, 28(19), pp. 1–7. Available at: https://doi.org/10.2352/issn.2470-1173.2016.19.coimg-155.

BibTeX
@article{venkatakrishnan2016making,
  title = {{Making Advanced Scientific Algorithms and Big Scientific Data Management More Accessible}},
  author = {Venkatakrishnan, Singanallur and Mohan, K. Aditya and Beattie, K. and Correa, Joaquin and Dart, Eli and Deslippe, Jack and Hexemer, Alexander and Krishnan, Harinarayan and MacDowell, Alastair A. and Marchesini, Stefano and Patton, Simon and Perciano, Talita and Sethian, James A. and Stromsness, Rune and Tierney, Brian L. and Tull, C. E. and Ushizima, Daniela and Parkinson, Dilworth Y.},
  journal = {Electronic Imaging},
  volume = {28},
  number = {19},
  pages = {1--7},
  year = {2016},
  doi = {10.2352/issn.2470-1173.2016.19.coimg-155}
}

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