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In the study of micro-swimmers, both artificial and biological ones,many-query problems arise naturally. Even with the use of advanced highperformance computing (HPC), it is not possible to solve this kind of problemsin an acceptable amount of time. Various approximations of the Stokes equationhave been considered in the past to ease such computational efforts but theyintroduce non-negligible errors that can easily make the solution of theproblem inaccurate and unreliable. Reduced order modeling solves this issue bytaking advantage of a proper subdivision between a computationally expensiveoffline phase and a fast and efficient online stage.  This work presents the coupling of Boundary Element Method (BEM) and ReducedBasis (RB) Reduced  Order Modeling (ROM) in two models of practical interest, obtaining accurateand reliable solutions to different many-query problems. Comparisons ofstandard reduced order modeling approaches in different simulation settings anda comparison to typical approximations to Stokes equations are also shown.Different couplings between a solver based on a HPC boundary element method formicro-motility problems and reduced order models are presented in detail. Themethodology is tested on two different models: a robotic-bacterium-like and anEukaryotic-like swimmer, and in each case two resolution strategies for theswimming problem, the split and monolithic one, are used as starting points forthe ROM. An efficient and accurate reconstruction of the performance ofinterest is achieved in both cases proving the effectiveness of our strategy.

MicroROM: An Efficient and Accurate Reduced Order Method to Solve Many-Query Problems in Micro-Motility