INMOST
INMOST is an open-source numerical simulation framework for developing multi-physics simulation applications. It provides tools for mesh generation, solving PDEs, post-processing results, and more. INMOST is focused on performance, scalability, and ease of use.
opensource
numerical-simulation
multiphysics
mesh-generation
pde-solving
postprocessing
performance
scalability
INMOST: Open-Source Multi-Physics Simulation Framework
INMOST is an open-source numerical simulation framework for developing multi-physics simulation applications. It provides tools for mesh generation, solving PDEs, post-processing results, and more. INMOST is focused on performance, scalability, and ease of use.
What is INMOST?
INMOST is an open-source framework designed for developing numerical simulation applications, with a focus on performance, scalability, and ease of use. It provides a set of reusable components for common tasks in numerical simulations, including:
- Mesh generation and partitioning for parallel computations
- Solvers for systems of partial differential equations (PDEs)
- Tools for parallel input/output and data visualization
- Interfaces to external libraries like PETSc, Trilinos, HYPRE, etc.
Some key highlights of INMOST include:
- Support for parallel distributed-memory computations and domain decomposition methods
- Dynamic load balancing for better scalability
- Python scripting interface for rapid development
- MODULAR code design allowing easy extension and customization
- APIs for coupling multiple physics simulations
- Integrated visualization powered by ParaView
INMOST can be used to create simulators for problems in computational fluid dynamics, structural mechanics, electromagnetics, and more. Its parallel capabilities allow large complex multi-physics models to utilize high performance computing resources efficiently. The open-source model promotes collaboration and continuous improvement of the platform.
INMOST Features
Features
- Unstructured mesh generation and processing
- Solvers for systems of PDEs
- Parallel scalable solvers using MPI
- Post-processing and visualization
- Python scripting interface
- Modular architecture
Pricing
- Open Source
Pros
Open source and free
High performance and scalability
Support for complex physics and parallel computing
Python scripting for rapid development
Active development community
Cons
Limited documentation and examples
Steep learning curve
Lacks GUI and ease of use features
Mostly focused on research applications
Official Links
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