TY - JOUR
T1 - Making advanced scientific algorithms and big scientific data management more accessible
AU - Venkatakrishnan, S. V.
AU - Mohan, K. Aditya
AU - Beattie, Keith
AU - Correa, Joaquin
AU - Dart, Eli
AU - Deslippe, Jack R.
AU - Hexemer, Alexander
AU - Krishnan, Harinarayan
AU - MacDowell, Alastair A.
AU - Marchesini, Stefano
AU - Patton, Simon J.
AU - Perciano, Talita
AU - Sethian, James A.
AU - Stromsness, Rune
AU - Tierney, Brian L.
AU - Tull, Craig E.
AU - Ushizima, Daniela
AU - Parkinson, Dilworth Y.
N1 - Publisher Copyright:
© 2016 Society for Imaging Science and Technology.
PY - 2016
Y1 - 2016
N2 - 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).
AB - 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).
UR - http://www.scopus.com/inward/record.url?scp=85046053523&partnerID=8YFLogxK
U2 - 10.2352/ISSN.2470-1173.2016.19.COIMG-155
DO - 10.2352/ISSN.2470-1173.2016.19.COIMG-155
M3 - Conference article
AN - SCOPUS:85046053523
SN - 2470-1173
JO - IS and T International Symposium on Electronic Imaging Science and Technology
JF - IS and T International Symposium on Electronic Imaging Science and Technology
T2 - Computational Imaging XIV 2016
Y2 - 14 February 2016 through 18 February 2016
ER -