SC17 Denver, CO

A Highly Scalable, Algorithm-Based Fault-Tolerant Solver for Gyrokinetic Plasma Simulations

Workshop: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems
Authors: Michael Obersteiner (Technical University Munich)

Abstract: With future exascale computers expected to have millions of compute units distributed among thousands of nodes, system faults are predicted to become more frequent. Fault tolerance will thus play a key role in HPC at this scale. In this presentation, we focus on solving the 5-dimensional gyrokinetic Vlasov-Maxwell equations using the application code GENE as it represents a high-dimensional and resource-intensive problem which is a natural candidate for exascale computing. We discuss the Fault-Tolerant Combination Technique, a resilient version of the Combination Technique, a method to increase the discretization resolution of existing PDE solvers. For the first time, we present an efficient, scalable and fault-tolerant implementation of this algorithm for plasma physics simulations based on a manager-worker model and test it under very realistic and pessimistic environments with simulated faults. We show that the Fault-Tolerant Combination Technique – an algorithm-based forward recovery method – can tolerate a large number of faults with a low overhead and at an acceptable loss in accuracy. Our parallel experiments with up to 32k cores show good scalability at a relative parallel efficiency of 93.61%. We conclude that algorithm-based solutions to fault tolerance are attractive for this type of problem.

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