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Cosmological simulations require the use of a multiple time-stepping scheme.Without such a scheme, cosmological simulations would be impossible due totheir high level of dynamic range; over eleven orders of magnitude in density.Such a large dynamic range leads to a range of over four orders of magnitude intime-step, which presents a significant load-balancing challenge. In this work,the extreme adaptivity that cosmological simulations present is tackled inthree main ways through the use of the code SWIFT. First, an adaptive mesh isused to ensure that only the relevant particles are interacted in a giventime-step. Second, task-based parallelism is used to ensure efficientload-balancing within a single node, using pthreads and SIMD vectorisation.Finally, a domain decomposition strategy is presented, using the graph domaindecomposition library METIS, that bisects the work that must be performed bythe simulation between nodes using MPI. These three strategies are shown togive SWIFT near-perfect weak-scaling characteristics, only losing 25%performance when scaling from 1 to 4096 cores on a representative problem,whilst being more than 30x faster than the de-facto standard Gadget-2 code.

SWIFT: Maintaining weak-scalability with a dynamic range of $10^4$ in time-step size to harness extreme adaptivity