Abstract
INMOST (Integrated Numerical Modeling Object-oriented Supercomputing Technologies) is an open-source platform for fast development of efficient and flexible parallel multi-physics models. In this paper we review capabilities of the platform and present two INMOST-based applications for parallel simulations of multi-phase flow in porous media and clot formation in blood flow. For a more detailed description we refer to [1].
The finite volume (FV) method is the popular approach to spatial discretizations on general meshes (i.e. meshes composed of general polyhedral cells), especially for geophysical and biomedical applications where local mass conservation is vital. INMOST provides a complete set of tools for development of FV discretizations for linear and nonlinear problems: automatic differentiation tool for assembly of the nonlinear residual and corresponding Jacobian and Hessian matrices, iterative solvers of nonlinear systems arising from PDEs discretization, parallel solvers for sparse linear algebraic systems.
The platform also provides a technology for development of numerical models on general unstructured grids. It includes parallel mesh data structures, low-level infrastructure for reading, writing, creating, manipulating and partitioning of distributed general meshes.
The synergy of INMOST platform and efficient FV discretizations for systems of PDEs on general meshes produces a powerful tool for supercomputing simulations.
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Acknowledgements
This work has been supported by the RAS Research program No. 26 “Basics of algorithms and software for high performance computing” and RFBR grant 18-31-20048 “Mathematical models of coronary blood flows and thrombogenic processes in cardiac pathologies”.
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Terekhov, K., Nikitin, K., Vassilevski, Y. (2020). INMOST Platform for Parallel Multi-physics Applications: Multi-phase Flow in Porous Media and Blood Flow Coagulation. In: Voevodin, V., Sobolev, S. (eds) Supercomputing. RuSCDays 2020. Communications in Computer and Information Science, vol 1331. Springer, Cham. https://doi.org/10.1007/978-3-030-64616-5_20
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