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Implementation of 2D Domain Decomposition in the UCAN Gyrokinetic Particle-in-Cell Code and Resulting Performance of UCAN2

Published online by Cambridge University Press:  15 January 2016

Jean-Noel G. Leboeuf ,
Viktor K. Decyk ,
David E. Newman  and
Raul Sanchez
Jean-Noel G. Leboeuf*
Affiliation:
Department of Physics, University of Alaska, Fairbanks, AK 99775-5920, USA
Viktor K. Decyk
Affiliation:
Department of Physics and Astronomy, and Institute for Digital Research and Education (IDRE), University of California, Los Angeles, CA 90095-1547, USA
David E. Newman
Affiliation:
Department of Physics, University of Alaska, Fairbanks, AK 99775-5920, USA
Raul Sanchez
Affiliation:
Departamento de Fsica, Universidad Carlos III, Leganes 28911, Madrid, Spain
*
*Corresponding author. Email addresses:[email protected] (J.-N. G. Leboeuf), [email protected] (V. K. Decyk), [email protected] (D. E. Newman), [email protected] (R. Sanchez)
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Abstract

The massively parallel, nonlinear, three-dimensional (3D), toroidal, electrostatic, gyrokinetic, particle-in-cell (PIC), Cartesian geometry UCAN code, with particle ions and adiabatic electrons, has been successfully exercised to identify non-diffusive transport characteristics in present day tokamak discharges. The limitation in applying UCAN to larger scale discharges is the 1D domain decomposition in the toroidal (or z-) direction for massively parallel implementation using MPI which has restricted the calculations to a few hundred ion Larmor radii or gyroradii per plasma minor radius. To exceed these sizes, we have implemented 2D domain decomposition in UCAN with the addition of the y-direction to the processor mix. This has been facilitated by use of relevant components in the P2LIB library of field and particle management routines developed for UCLA's UPIC Framework of conventional PIC codes. The gyro-averaging specific to gyrokinetic codes is simplified by the use of replicated arrays for efficient charge accumulation and force deposition. The 2D domain-decomposed UCAN2 code reproduces the original 1D domain nonlinear results within round-off. Benchmarks of UCAN2 on the Cray XC30 Edison at NERSC demonstrate ideal scaling when problem size is increased along with processor number up to the largest power of 2 available, namely 131,072 processors. These particle weak scaling benchmarks also indicate that the 1 nanosecond per particle per time step and 1 TFlops barriers are easily broken by UCAN2 with 1 billion particles or more and 2000 or more processors.

Keywords

Gyrokinetic simulationparticle-in-cell methodmassive parallelization
Type
Research Article
Information
Communications in Computational Physics , Volume 19 , Issue 1 , January 2016 , pp. 205 - 225
Copyright
Copyright © Global-Science Press 2016 

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