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Abstract

Atomistic simulations of large biomolecular systems with chemicalvariability such as constant pH dynamic protonation offer multiple challenges inhigh performance computing. One of them is the correct treatment of the involvedelectrostatics in an efficient and highly scalable way. Here we review and assess twoof the main building blocks that will permit such simulations: (1) An electrostaticslibrary based on the Fast Multipole Method (FMM) that treats local alternativecharge distributions with minimal overhead, and (2) Aλ-dynamics module workingin tandem with the FMM that enables various types of chemical transitions duringthe simulation. Ourλ-dynamics and FMM implementations do not rely on third-party libraries but are exclusively using C++ language features and they aretailored to the specific requirements of molecular dynamics simulation suites suchas GROMACS. The FMM library supports fractional tree depths and allows forrigorous error control and automatic performance optimization at runtime. Near-optimal performance is achieved on various SIMD architectures and on GPUsusing CUDA. For exascale systems, we expect our approach to outperform currentimplementations based on Particle MeshEwald (PME) electrostatics, becauseFMM avoids the communication bottlenecks caused by the parallel fast Fouriertransformations needed for PME.