82 research outputs found
Solving the Vlasov equation for one-dimensional models with long range interactions on a GPU
We present a GPU parallel implementation of the numeric integration of the
Vlasov equation in one spatial dimension based on a second order time-split
algorithm with a local modified cubic-spline interpolation. We apply our
approach to three different systems with long-range interactions: the
Hamiltonian Mean Field, Ring and the self-gravitating sheet models. Speedups
and accuracy for each model and different grid resolutions are presented
A "metric" semi-Lagrangian Vlasov-Poisson solver
We propose a new semi-Lagrangian Vlasov-Poisson solver. It employs elements
of metric to follow locally the flow and its deformation, allowing one to find
quickly and accurately the initial phase-space position of any test
particle , by expanding at second order the geometry of the motion in the
vicinity of the closest element. It is thus possible to reconstruct accurately
the phase-space distribution function at any time and position by
proper interpolation of initial conditions, following Liouville theorem. When
distorsion of the elements of metric becomes too large, it is necessary to
create new initial conditions along with isotropic elements and repeat the
procedure again until next resampling. To speed up the process, interpolation
of the phase-space distribution is performed at second order during the
transport phase, while third order splines are used at the moments of
remapping. We also show how to compute accurately the region of influence of
each element of metric with the proper percolation scheme. The algorithm is
tested here in the framework of one-dimensional gravitational dynamics but is
implemented in such a way that it can be extended easily to four or
six-dimensional phase-space. It can also be trivially generalised to plasmas.Comment: 32 pages, 14 figures, accepted for publication in Journal of Plasma
Physics, Special issue: The Vlasov equation, from space to laboratory plasma
Evaluating kernels on Xeon Phi to accelerate Gysela application
This work describes the challenges presented by porting parts ofthe Gysela
code to the Intel Xeon Phi coprocessor, as well as techniques used for
optimization, vectorization and tuning that can be applied to other
applications. We evaluate the performance of somegeneric micro-benchmark on Phi
versus Intel Sandy Bridge. Several interpolation kernels useful for the Gysela
application are analyzed and the performance are shown. Some memory-bound and
compute-bound kernels are accelerated by a factor 2 on the Phi device compared
to Sandy architecture. Nevertheless, it is hard, if not impossible, to reach a
large fraction of the peek performance on the Phi device,especially for
real-life applications as Gysela. A collateral benefit of this optimization and
tuning work is that the execution time of Gysela (using 4D advections) has
decreased on a standard architecture such as Intel Sandy Bridge.Comment: submitted to ESAIM proceedings for CEMRACS 2014 summer school version
reviewe
Hermite spline interpolation on patches for a parallel solving of the Vlasov-Poisson equation
Ce travail concerne la résolution numérique de l'équation de Vlasov en utilisant une grille de l'espace des phases. Contrairement aux méthodes PIC qui sont connues pour etre bruitée, nous proposons une méthode basée sur la méthode semi-lagrangienne pour discrétiser l'équation de Vlasov en 2 dimensions de l'espace des phases. Ce type de méthode étant très couteuse numériquement, on propose d'effectuer les simulations sur des machines parallèles. Pour cela, on présente une méthode de décomposition de domaine, chaque sous-domaine étant dédié à un processeur. Des conditions de type Hermite aux bords permettent alors d'obtenir une bonne approximation de la solution globale. Plusieurs résultats numériques montrent la précision et la bonne scalabilité de la méthode jusqu'à 64 processeurs
A massively parallel semi-Lagrangian solver for the six-dimensional Vlasov-Poisson equation
This paper presents an optimized and scalable semi-Lagrangian solver for the
Vlasov-Poisson system in six-dimensional phase space. Grid-based solvers of the
Vlasov equation are known to give accurate results. At the same time, these
solvers are challenged by the curse of dimensionality resulting in very high
memory requirements, and moreover, requiring highly efficient parallelization
schemes. In this paper, we consider the 6d Vlasov-Poisson problem discretized
by a split-step semi-Lagrangian scheme, using successive 1d interpolations on
1d stripes of the 6d domain. Two parallelization paradigms are compared, a
remapping scheme and a classical domain decomposition approach applied to the
full 6d problem. From numerical experiments, the latter approach is found to be
superior in the massively parallel case in various respects. We address the
challenge of artificial time step restrictions due to the decomposition of the
domain by introducing a blocked one-sided communication scheme for the purely
electrostatic case and a rotating mesh for the case with a constant magnetic
field. In addition, we propose a pipelining scheme that enables to hide the
costs for the halo communication between neighbor processes efficiently behind
useful computation. Parallel scalability on up to 65k processes is demonstrated
for benchmark problems on a supercomputer
An arbitrary curvilinear coordinate particle in cell method
A new approach to the kinetic simulation of plasmas in complex geometries, based on the Particle-in-Cell (PIC) simulation method, is explored. In this method, called the Arbitrary Curvilinear Coordinate PIC (ACC-PIC) method, all essential PIC operations are carried out on a uniform, unitary square logical domain and mapped to a nonuniform, boundary fitted physical domain. We utilize an elliptic grid generation technique known as Winslow\u27s method to generate boundary-fitted physical domains. We have derived the logical grid macroparticle equations of motion based on a canonical transformation of Hamilton\u27s equations from the physical domain to the logical. These equations of motion are not seperable, and therefore unable to be integrated using the standard Leapfrog method. We have developed an extension of the semi-implicit Modified Leapfrog (ML) integration technique to preserve the symplectic nature of the logical grid particle mover. We constructed a proof to show that the ML integrator is symplectic for systems of arbitrary dimension. We have constructed a generalized, curvilinear coordinate formulation of Poisson\u27s equations to solve for the electrostatic fields on the uniform logical grid. By our formulation, we supply the plasma charge density on the logical grid as a source term. By the formulations of the logical grid particle mover and the field equations, the plasma particles are weighted to the uniform logical grid and the self-consistent mean fields obtained from the solution of the Poisson equation are interpolated to the particle position on the logical grid. This process coordinates the complexity associated with the weighting and interpolation processes on the nonuniform physical grid. In this work, we explore the feasibility of the ACC-PIC method as a first step towards building a production level, time-adaptive-grid, 3D electromagnetic ACC-PIC code. We begin by combining the individual components to construct a 1D, electrostatic ACC-PIC code on a stationary nonuniform grid. Several standard physics tests were used to validate the accuracy of our method in comparison with a standard uniform grid PIC code. We then extend the code to two spatial dimensions and repeat the physics tests on a rectangular domain with both orthogonal and nonorthogonal meshing in comparison with a standard 2D uniform grid PIC code. As a proof of principle, we then show the time evolution of an electrostatic plasma oscillation on an annular domain obtained using Winslow\u27s method
SPACE: 3D Parallel Solvers for Vlasov-Maxwell and Vlasov-Poisson Equations for Relativistic Plasmas with Atomic Transformations
A parallel, relativistic, three-dimensional particle-in-cell code SPACE has
been developed for the simulation of electromagnetic fields, relativistic
particle beams, and plasmas. In addition to the standard second-order
Particle-in-Cell (PIC) algorithm, SPACE includes efficient novel algorithms to
resolve atomic physics processes such as multi-level ionization of plasma
atoms, recombination, and electron attachment to dopants in dense neutral
gases. SPACE also contains a highly adaptive particle-based method, called
Adaptive Particle-in-Cloud (AP-Cloud), for solving the Vlasov-Poisson problems.
It eliminates the traditional Cartesian mesh of PIC and replaces it with an
adaptive octree data structure. The code's algorithms, structure, capabilities,
parallelization strategy and performances have been discussed. Typical examples
of SPACE applications to accelerator science and engineering problems are also
presented.Comment: 12 pages, 7 figure
- …