The massively parallel,nonlinear,three-dimensional(3D),toroidal,electrostatic,gyrokinetic,particle-in-cell(PIC),Cartesian geometry UCANcode,with particle ions and adiabatic electrons,has been successfully exercised to...The massively parallel,nonlinear,three-dimensional(3D),toroidal,electrostatic,gyrokinetic,particle-in-cell(PIC),Cartesian geometry UCANcode,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 UCANwith 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 gyroaveraging 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.展开更多
基金This work was supported in part in the USA by Grant No.DE-FG02-04ER54741 to the University of Alaska,Fairbanks,AK,from the Office of Fusion Energy Sciences,Office of Science,United States Department of EnergyIt was also supported in part at Univer-sidad Carlos III,Madrid,Spain,by Spanish National Project No.ENE2009-12213-C03-03+1 种基金This research used resources of the National Energy Research Scientific Computing Center(NERSC)which is supported by the Office of Science of the U.S.Department of Energy under Contract No.DE-AC02-05CH11231.
文摘The massively parallel,nonlinear,three-dimensional(3D),toroidal,electrostatic,gyrokinetic,particle-in-cell(PIC),Cartesian geometry UCANcode,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 UCANwith 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 gyroaveraging 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.
