GromEx: Highly Scalable Unified Long-Range Electrostatics and Flexible Ionization for Realistic Biomolecular Simulations on the Exascale

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Computer simulations on the basis of theoretical physics and chemistry have grown to be invaluable tools of scientific research on molecular function and structure. Such simulations share common challenges with simulations on other strongly interacting systems, e.g. in astrophysics. Advancing the field of molecular simulation to exascale computing is thus highly beneficial to science and the public. The most costly part of molecular simulations is the computation of electrostatic long-range interactions. Thus, the efficiency of calculating these interactions is decisive for the whole simulation. Molecular electrostatics is complicated by the fact that molecules can contain titratable sites whose charge distribution varies over time. This variability originates, e.g., from protonation or redox reactions, or binding of different drug molecules. These reactions are intricately coupled to electrostatics as well as crucial for the function and interaction properties of many (bio)molecules. Thus, a realistic treatment of electrostatics in biomolecular simulation has to account for the different forms of titratable sites. The particle mesh Ewald method (PME, currently state of the art in molecular simulation) does not scale to large core counts as it suffers from a communication bottleneck, and does not treat titratable sites efficiently. In this project, we combine a fast multipole method (FMM) with a lambda-dynamics method to both alleviate the PME bottleneck and, for the first time, enable realistic chemical variability of titratable sites in molecular simulations. The FMM will enable an efficient calculation of long-range interactions on massively parallel exascale computers, including alternative charge distributions representing various forms of titratable sites. lambda-dynamics allows for a smooth interconversion between site forms during the simulation which is indispensable for efficient, fully atomistic molecular simulations. In the second funding period, we aim to open up a whole new application range for molecular simulation, both in terms of the hardware that can be utilized at optimum performance and in terms of the type of scientific problems that can be addressed. In detail we will: 1. Extend the current code to allow for multiple local topologies of each site. This will let simulations account for the whole range of variability of titratable sites instead of just protonation 2. Enable our solver to take full advantage of future exascale hardware including many-core CPUs and accelerators like GPUs or Xeon Phi coprocessors 3. For optimum scaling on this heterogeneous hardware, we will design and implement a graph- based partitioning scheme to choose from algorithmic alternatives according to latency and throughput of the available hardware devices Example applications include computational drug design and simulations on the function of nanomachines.