Towards Heterogeneous Multi-scale Computing on Large Scale Parallel Supercomputers

Saad Alowayyed (1) , Maxime Vassaux (2) , Ben Czaja , Peter V Coveney (2) , Alfons G Hoekstra (3)

1 KACST - King Abdulaziz City for Science and Technology [Riyadh]
2 Department of Chemistry [UCL, London]
3 Computational Science Lab [Amsterdam]

New applications exploiting emerging exascale computing resources efficiently, while providing meaningful scientific results, are lagging behind. Multi-scale models, especially multi-scale applications, can potentially run on the exascale. We have established that a class of multi-scale applications implementing the heterogeneous multi-scale model follows, a heterogeneous multi-scale computing (HMC) pattern, which typically features a macroscopic model synchronising numerous independent microscopic model simulations. Consequently, communication between microscopic simulations is limited. Furthermore, a surrogate model can often be introduced between macroscale and micro-scale models to interpolate required data from previously computed micro-scale simulations, thereby substantially reducing the number of micro-scale simulations. Nonetheless, HMC applications, though versatile, remain constrained by load balancing issues. We discuss two main issues: the a priori unknown and variable execution time of microscopic simulations, and the dynamic number of micro-scale simulations required. We tackle execution time variability using a pilot job mechanism to handle internal queuing and multiple sub-model execution on large-scale supercomputers, together with a data-informed execution time prediction model. To dynamically select the number of micro-scale simulations, the HMC pattern automatically detects and identifies three surrogate model phases that help control available and used core amount. After relevant phase detection and micro-scale simulation scheduling, any idle cores can be used for surrogate model update or for processor release back to the system. We demonstrate HMC performance by testing it on two representative multi-scale applications. We conclude that, considering the subtle interplay between the macroscale model, surrogate models and micro-scale simulations, HMC provides a promising path towards exascale for many multi-scale applications.

Mots clés: multi-scale modelling; surrogate model; computational science; heterogeneous multiscale computing; high performance computing; exascale

Domaines: Bio-informatique [q-bio.QM]; Modélisation et simulation; Calcul parallèle, distribué et partagé [cs.DC]; Matériaux composites et construction; Matériaux; Mécanique des structures [physics.class-ph]; Mécanique des matériaux [physics.class-ph]

Saad Alowayyed, Maxime Vassaux, Ben Czaja, Peter V Coveney, Alfons G Hoekstra. Towards Heterogeneous Multi-scale Computing on Large Scale Parallel Supercomputers. Supercomputing Frontiers and Innovations , 2019, 6 (4), ⟨10.14529/jsfi190402⟩. ⟨hal-03472287⟩