Design
Structure
The high-level directory structure delineates the types of microphysics and the generic solvers:
conductivity/
: thermal conductivity routinesconstants/
: fundamental constantsDocs/
: the sphinx source for this documentationEOS/
: the various equations of stateintegration/
: the ODE integration routines used for the reaction networksinterfaces/
: the main structs / derived types that are used to interface with the EOS and reaction networks.networks/
: the nuclear reaction networks. This is mostly just the righthand side of the network, as the actual integrators are decoupled from the network.neutrinos/
: neutrino loss source terms for the network energy equation.opacity/
: opacity routines for radiation transportrates/
: common nuclear reaction rate modules used by some of the networks.screening/
: common electron screening factors used by some of the reaction networks.unit_test/
: self-contained unit tests for Microphysics. These don’t need any application code to build, but will require AMReX.util/
: linear algebra solvers and other routines.
Note
All quantities are assumed to be in CGS units, unless otherwise specified.
Design philosophy
Any application that uses Microphysics will at minimum need to
choose an EOS and a network. These two components work together. The
design philosophy is that the EOS depends on the network, but not the
other way around. The decision was made for the network to act as the
core module, and lots of code depends on it. This avoids circular
dependencies by having the main EOS datatype, eos_t
, and the
main reaction network datatype, burn_t
, be built on top of the
network.
The network is meant to store the properties of the species (typically nuclear isotopes) including their atomic weights and numbers, and also describes any links between the species when burning.
The equation of state relates the thermodynamic properties of the material. It depends on the composition of the material, typically specified via mass fractions of the species, and uses the properties of the species defined by the network to interpret the state.
We try to maximize code reuse in the Microphysics source, so the solvers (ODE integration for the network and Newton-Raphson root finding for the EOS) are separated from the specific implementations of the microphysics.
GPU considerations
All of the Microphysics routines are written to run on GPUs. This is enabled in application codes by using the AMReX lambda-capturing mechanism (see the AMReX GPU documentation for more information).
This means leveraging the AMReX data-structures, macros, and functions. The unit tests (see Overview of Unit Tests) provide a good reference for how to interface the Microphysics solvers and physics terms with an AMReX-based code.
There are a few places where Microphysics behaves slightly differently when running on a CPU vs. a GPU:
In the VODE integrator, we disable Jacobian-caching to save memory. See ODE Integrators.
In general we disable printing from GPU kernels, due to register pressure. Some output can be enabled by compiling with
USE_GPU_PRINTF=TRUE
.