TY - JOUR
T1 - PANORAMA
T2 - An approach to performance modeling and diagnosis of extreme-scale workflows
AU - Deelman, Ewa
AU - Carothers, Christopher
AU - Mandal, Anirban
AU - Tierney, Brian
AU - Vetter, Jeffrey S.
AU - Baldin, Ilya
AU - Castillo, Claris
AU - Juve, Gideon
AU - Król, Dariusz
AU - Lynch, Vickie
AU - Mayer, Ben
AU - Meredith, Jeremy
AU - Proffen, Thomas
AU - Ruth, Paul
AU - Ferreira da Silva, Rafael
N1 - Publisher Copyright:
© The Author(s) 2015.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Thus, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation and data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.
AB - Computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Thus, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation and data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.
KW - Performance modeling
KW - extreme scale
KW - scientific workflow
UR - http://www.scopus.com/inward/record.url?scp=85008474111&partnerID=8YFLogxK
U2 - 10.1177/1094342015594515
DO - 10.1177/1094342015594515
M3 - Article
AN - SCOPUS:85008474111
SN - 1094-3420
VL - 31
SP - 4
EP - 18
JO - International Journal of High Performance Computing Applications
JF - International Journal of High Performance Computing Applications
IS - 1
ER -