Abstract
Fast, accurate three dimensional reconstructions of plasma equilibria, crucial for physics interpretation of fusion data generated within confinement devices like stellarators/ tokamaks, are computationally very expensive and routinely require days, even weeks, to complete using serial approaches. Here, we present a parallel implementation of the three dimensional plasma reconstruction code, V3FIT. A formal analysis to identify the performance bottlenecks and scalability limits of this new parallel implementation, which combines both task and data parallelism, is presented. The theoretical findings are supported by empirical performance results on several thousands of processor cores of a Cray XC30 supercomputer. Parallel V3FIT is shown to deliver over 40X speedup, enabling fusion scientists to carry out three dimensional plasma equilibrium reconstructions at unprecedented scales in only a few hours (instead of in days/weeks) for the first time.
Original language | English |
---|---|
Title of host publication | Proceedings - 46th International Conference on Parallel Processing, ICPP 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 282-291 |
Number of pages | 10 |
ISBN (Electronic) | 9781538610428 |
DOIs | |
State | Published - Sep 1 2017 |
Event | 46th International Conference on Parallel Processing, ICPP 2017 - Bristol, United Kingdom Duration: Aug 14 2017 → Aug 17 2017 |
Publication series
Name | Proceedings of the International Conference on Parallel Processing |
---|---|
ISSN (Print) | 0190-3918 |
Conference
Conference | 46th International Conference on Parallel Processing, ICPP 2017 |
---|---|
Country/Territory | United Kingdom |
City | Bristol |
Period | 08/14/17 → 08/17/17 |
Funding
This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). This material is based upon work supported by the U.S. Department of Energy, Office of Fusion Energy Sciences under contract number DE-AC05-00OR22725. This research used resources at the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility operated by the Oak Ridge National Laboratory.