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add package for feelpp #4
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var/spack/repos/builtin/packages/feelpp/package.py

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class Feelpp(CMakePackage):
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"""
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Feel++ is an Open-Source C++ library designed to solve a wide range of partial differential equations (PDEs) using advanced Galerkin methods.
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These methods include the finite element method (FEM), spectral element method, discontinuous Galerkin methods, and reduced basis methods.
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Feel++ is optimized for high-performance computing, enabling seamless parallel computing on large-scale systems, ranging from desktop machines to supercomputers with tens of thousands of cores.
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The library supports multi-physics simulations and provides a modular structure to simplify the development of applications.
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Key Features:
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- **Toolboxes**: Predefined toolboxes for common PDE problems, enabling faster development and deployment of complex simulations. These toolboxes include:
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- **Coefficient Form PDEs**: For general PDEs in coefficient form.
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- **Computational Solid Mechanics**: For simulations of solid mechanics problems.
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- **Computational Fluid Mechanics**: For solving fluid dynamics problems.
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- **Heat Transfer**: For heat conduction and convection problems.
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- **Heat & Fluid**: Coupled heat and fluid dynamics simulations.
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- **Fluid Structure Interaction (FSI)**: For problems involving interactions between fluid flow and structural mechanics.
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- **Electric**: For solving electric field and current problems.
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- **Thermo-Electric**: For coupled thermoelectric simulations.
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- **Maxwell**: For simulating electromagnetic field problems based on Maxwell's equations.
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- **Hybridized Discontinuous Galerkin**: For high-order accurate discontinuous Galerkin methods with hybridization techniques.
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- **Model Order Reduction (MOR)**: Provides efficient techniques for reducing the computational complexity of large-scale simulations, enabling faster simulations while maintaining accuracy.
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- **Python Wrappers**: Python bindings allow for seamless integration of Feel++ functionalities into Python-based workflows, enabling rapid prototyping, interactive simulations, and data visualization.
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- **High-Performance Computing (HPC)**: Fully optimized for distributed (MPI) and shared-memory (multithread) parallelism, Feel++ can efficiently scale from small multi-core systems to large HPC clusters.
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- **C++ Standards**: Support for C++17, C++20, and C++23 standards, allowing users to leverage modern language features and optimizations.
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- **Extensive Scientific Libraries Integration**: Feel++ integrates with major scientific computing libraries, including PETSc, SLEPc, Boost, FFTW, and others, to extend its functionality and scalability.
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Optional Variants:
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- **+toolboxes**: Enable specialized toolboxes for common PDEs, such as fluid mechanics, solid mechanics, and coupled heat and fluid simulations.
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- **+mor**: Enable Model Order Reduction (MOR) for computationally expensive large-scale systems.
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- **+python**: Enable Python bindings to allow Python-based interaction with Feel++.
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- **+quickstart**: Enable quickstart examples for easier onboarding and usage.
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- **+tests**: Enable tests to verify the integrity of the Feel++ installation.
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- **cpp17/cpp20/cpp23**: Choose the C++ standard (C++17, C++20, or C++23) for compilation.
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Feel++ is an Open-Source C++ library designed to solve a wide range of
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partial differential equations (PDEs) using advanced Galerkin methods.
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These methods include the finite element method (FEM), spectral element
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method, discontinuous Galerkin methods, and reduced basis methods.
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Feel++ is optimized for high-performance computing, enabling seamless
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parallel computing on large-scale systems, ranging from desktop machines
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to supercomputers with tens of thousands of cores. The library supports
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multi-physics simulations and provides a modular structure to simplify
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the development of applications.
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"""
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