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Experimental AMR library for hyperbolic PDEs in Rust

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gridiron

Gridiron is an adaptive mesh refinement (AMR) library for solving time-dependent systems of conservation laws, like the Euler equations of gas dynamics. It uses structured, rectilinear grid patches in the style of Berger-Oliger AMR, where patches can be placed at different refinement levels in flexible configurations: patches may overlap one another and fine patches may cross coarse patch boundaries. This is in contrast to more constrained quad-tree / oct-tree mesh topologies used e.g. in the Flash code.

This library is a work-in-progress in early stages. Its goals are:

  • Provide meshing and execution abstractions for hydrodynamics base schemes. If you have a scheme that works on logically Cartesian grid patches, this library can make that scheme suitable for AMR simulations.
  • Be aggressively optimized in terms of computations, array traversals (no multi-dimensional indexing), and memory access patterns (optimal cache + heap utilization).
  • Provide efficient strategies for hybrid parallelization based on shared memory and distributed multi-processing.
  • Have minimal dependencies. The library can be used without any outside crates. Optional dependences include rayon (for its thread pool, although a custom thread pool is also included), serde (for message passing and checkpoints). Optional features that only effect performance are crossbeam_channel and core_affinity. The examples/euler sub-crate demonstrates ues of all the optional features.
  • Have fast compile times. The debug cycle for physics simulations often requires frequent recompilation and inspection of results. Compile times of 1-2 seconds are fine, but the code should not take 30 seconds to compile, as can happen with excessive use of generics, async, link-time optimizations, etc. For this reason the primary data structure (patch::Patch) is not generic over an array element type; it uses f64 and a runtime-specified number of fields per grid cell location. It's encouraged to keep solver and physics code together in the same crate as the science application, because it allows rustc to optimize these modules together without link-time optimizations. There isn't much compute-intensive work done in the gridiron library functions, so there's no performance penalties for using it as a separate crate.
  • Provide examples of stand-alone applications which use the library.

It does not attempt to

  • Be a complete application framework. Data input/output, user configurations, visualization and post-processing should be handled by separate crates or by applications written for a specific science problem.
  • Provide lots of physics. The library will be written to facilitate multi-physics science applications that may require MHD, tracer particles, radiative transfer, self-gravity, and reaction networks. However, this library does not try to implement these things. The focus is the meshing and parallelization.

Building with MPI (optional)

MPI is not required for distributed parallel calculations, because there is a built-in message-passing module based on TCP sockets.

If you want to use MPI on an HPC cluster, just make sure you've loaded one of their MPI modules with e.g. module load mpi, and you're using the same MPI version at run time as when you build the code.

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Experimental AMR library for hyperbolic PDEs in Rust

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