Load Balancing for Massively Parallel Computations with the Sparse Grid Combination Technique
Mario Heene, Christoph Kowitz, Pflüger Dirk · Advances in parallel computing · 2014
Massively parallel simulations of plasma microturbulence using GENE are facing the curse of dimensionality, since the discretization of the five-dimensional gyrokinetic equations requires a large amount of grid points even for only moderate resolutions. The sparse grid combination technique can be used to tackle the curse of dimensionality. Being based on a superposition of anisotropic full grid solutions that can be computed independently of each other, it introduces a second layer of parallelism that will equip GENE for exascale computing. Since the anisotropy of the discretizations of the partial solutions results in massive load imbalances, effective scheduling is crucial in order to exploit this parallelism. In this paper a load model for linear initial value runs with GENE is introduced for effective load balancing for the combination technique.