In this paper, we propose a μ-mode integrator for computing the solution of stiff evolution equations. The integrator is based on a d-dimensional splitting approach and uses exact (usually precomputed) one-dimensional matrix exponentials. We show that the action of the exponentials, i.e. the corresponding batched matrix-vector products, can be implemented efficiently on modern computer systems. We further explain how μ-mode products can be used to compute spectral transforms efficiently even if no fast transform is available. We illustrate the performance of the new integrator by solving, among the others, three-dimensional linear and nonlinear Schrödinger equations, and we show that the μ-mode integrator can significantly outperform numerical methods well-established in the field. We also discuss how to efficiently implement this integrator on both multi- core CPUs and GPUs. Finally, the numerical experiments show that using GPUs results in performance improvements between a factor of 10 and 20, depending on the problem.

A μ-mode integrator for solving evolution equations in Kronecker form

Caliari, Marco;Cassini, Fabio;Einkemmer, Lukas;Ostermann, Alexander;Zivcovich, Franco
2022

Abstract

In this paper, we propose a μ-mode integrator for computing the solution of stiff evolution equations. The integrator is based on a d-dimensional splitting approach and uses exact (usually precomputed) one-dimensional matrix exponentials. We show that the action of the exponentials, i.e. the corresponding batched matrix-vector products, can be implemented efficiently on modern computer systems. We further explain how μ-mode products can be used to compute spectral transforms efficiently even if no fast transform is available. We illustrate the performance of the new integrator by solving, among the others, three-dimensional linear and nonlinear Schrödinger equations, and we show that the μ-mode integrator can significantly outperform numerical methods well-established in the field. We also discuss how to efficiently implement this integrator on both multi- core CPUs and GPUs. Finally, the numerical experiments show that using GPUs results in performance improvements between a factor of 10 and 20, depending on the problem.
Numerical solution of evolution equations, mu-mode product, Dimension splitting, Spectral transform, Schrödinger equation, Graphic processing unit (GPU
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11562/1056996
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