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µGrid

µGrid is a C++ library for discrete representation of fields on structured grids, with Python bindings. It provides efficient data structures and algorithms for solving partial differential equations on regular grids, with support for MPI parallelization and GPU acceleration.

Features

  • Field collections: Manage scalar, vector, and tensor fields on structured grids with flexible memory layouts
  • Domain decomposition: Cartesian decomposition with ghost cell communication for stencil operations
  • Linear operators: Stencil convolutions, a hard-coded Laplacian, and FEM gradient/divergence operators for linear simplex (P1) and multilinear (Q1) elements
  • Fused matrix-free operators: Problem-specific kernels that apply an operator, assemble its diagonal, or contract a sensitivity without ever forming a matrix or storing an intermediate field — for example isotropic linear elasticity on a regular grid
  • Iterative solvers: Preconditioned conjugate gradients, in a standard and a pipelined variant that overlaps its reductions
  • Preconditioners: Jacobi, Fourier (reference-stiffness/Green), its per-mode block form, and the combined Green-Jacobi preconditioner
  • Vector algebra: BLAS-like kernels on host and device (dot products, norms, axpy, scaling), including fused variants that return a reduction and update a vector in one pass
  • FFT engine: Built-in Fast Fourier Transform with MPI-parallel support (auto-selected slab or pencil decomposition) and native cuFFT/rocFFT N-D transforms on the GPU
  • GPU support: Optional CUDA and HIP backends. Fields, operators, solvers and preconditioners all run on device, so a solve need not return to the host; on unified-memory accelerators the allocator can be routed through managed memory
  • NetCDF I/O: Serial and parallel file I/O for checkpointing and analysis

µGrid is written in C++20 and has language bindings for Python via pybind11.

This README contains only a small quick start guide. Please refer to the full documentation for more help.

Quick start

To install µGrid, run

pip install muGrid

Note that on most platforms this will install a binary wheel, that was compiled with a minimal configuration. To compile for your specific platform use

pip install -v --no-binary muGrid muGrid

which will compile the code. µGrid will autodetect MPI. GPU support (CUDA/ROCm) is off by default and must be enabled explicitly at build time (see the documentation); it is not autodetected. For I/O, it will try to use Unidata NetCDF for serial builds and PnetCDF for MPI-parallel builds. Monitor output to see which of these options were automatically detected.

Funding

This development has received funding from the Swiss National Science Foundation, the European Research Council, and the Deutsche Forschungsgemeinschaft.

Release files for muGrid 1.4.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for muGrid 1.4.0
File Size Uploaded
mugrid-1.4.0.tar.gz 1.7 MB Details

Built distributions (wheels)

Table of built distributions (wheels) for muGrid 1.4.0
File
mugrid-1.4.0-cp314-cp314-win_arm64.whl CPython 3.14 CPython 3.14 Windows ARM64 Details
mugrid-1.4.0-cp314-cp314-win_amd64.whl CPython 3.14 CPython 3.14 Windows x86-64 Details
mugrid-1.4.0-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.14 CPython 3.14 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
mugrid-1.4.0-cp314-cp314-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.14 CPython 3.14 Linux glibc 2.28+ ARM64, Linux glibc 2.26+ ARM64 Details
mugrid-1.4.0-cp314-cp314-macosx_14_0_arm64.whl CPython 3.14 CPython 3.14 macOS 14.0+ ARM64 Details
mugrid-1.4.0-cp313-cp313-win_arm64.whl CPython 3.13 CPython 3.13 Windows ARM64 Details
mugrid-1.4.0-cp313-cp313-win_amd64.whl CPython 3.13 CPython 3.13 Windows x86-64 Details
mugrid-1.4.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.13 CPython 3.13 Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 Details
mugrid-1.4.0-cp313-cp313-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.13 CPython 3.13 Linux glibc 2.28+ ARM64, Linux glibc 2.26+ ARM64 Details
mugrid-1.4.0-cp313-cp313-macosx_14_0_arm64.whl CPython 3.13 CPython 3.13 macOS 14.0+ ARM64 Details
mugrid-1.4.0-cp312-cp312-win_arm64.whl CPython 3.12 CPython 3.12 Windows ARM64 Details
mugrid-1.4.0-cp312-cp312-win_amd64.whl CPython 3.12 CPython 3.12 Windows x86-64 Details
mugrid-1.4.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.12 CPython 3.12 Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 Details
mugrid-1.4.0-cp312-cp312-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.12 CPython 3.12 Linux glibc 2.26+ ARM64, Linux glibc 2.28+ ARM64 Details
mugrid-1.4.0-cp312-cp312-macosx_14_0_arm64.whl CPython 3.12 CPython 3.12 macOS 14.0+ ARM64 Details
mugrid-1.4.0-cp311-cp311-win_arm64.whl CPython 3.11 CPython 3.11 Windows ARM64 Details
mugrid-1.4.0-cp311-cp311-win_amd64.whl CPython 3.11 CPython 3.11 Windows x86-64 Details
mugrid-1.4.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.11 CPython 3.11 Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 Details
mugrid-1.4.0-cp311-cp311-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.11 CPython 3.11 Linux glibc 2.26+ ARM64, Linux glibc 2.28+ ARM64 Details
mugrid-1.4.0-cp311-cp311-macosx_14_0_arm64.whl CPython 3.11 CPython 3.11 macOS 14.0+ ARM64 Details
mugrid-1.4.0-cp310-cp310-win_arm64.whl CPython 3.10 CPython 3.10 Windows ARM64 Details
mugrid-1.4.0-cp310-cp310-win_amd64.whl CPython 3.10 CPython 3.10 Windows x86-64 Details
mugrid-1.4.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.10 CPython 3.10 Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 Details
mugrid-1.4.0-cp310-cp310-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl CPython 3.10 CPython 3.10 Linux glibc 2.26+ ARM64, Linux glibc 2.28+ ARM64 Details
mugrid-1.4.0-cp310-cp310-macosx_14_0_arm64.whl CPython 3.10 CPython 3.10 macOS 14.0+ ARM64 Details

Total release size: 135.0 MB

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Release files / mugrid-1.4.0-cp310-cp310-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl

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Release files / mugrid-1.4.0-cp310-cp310-macosx_14_0_arm64.whl

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This release

1.4.0 This release

26 release files

1.3.0

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1.2.0

24 release files

1.1.1

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1.0.0

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0.0.0

26 release files

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