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jan 2020-07-03 13:46:38 -07:00
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README.md
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@ -6,10 +6,10 @@ electromagnetic solver implemented in Python and OpenCL.
**Capabilities:**
* Arbitrary distributions of the following:
* Dielectric constant (```epsilon```)
* Magnetic permeabilty (```mu```)
* Perfect electric conductor (```PEC```)
* Perfect magnetic conductor (```PMC```)
* Dielectric constant (`epsilon`)
* Magnetic permeabilty (`mu`)
* Perfect electric conductor (`PEC`)
* Perfect magnetic conductor (`PMC`)
* Variable-sized rectangular grids
* Stretched-coordinate PMLs (complex cell sizes allowed)
@ -17,10 +17,10 @@ Currently, only periodic boundary conditions are included.
PEC/PMC boundaries can be implemented by drawing PEC/PMC cells near the edges.
Bloch boundary conditions are not included but wouldn't be very hard to add.
The default solver ```opencl_fdfd.cg_solver(...)``` located in main.py
The default solver `opencl_fdfd.cg_solver(...)` located in main.py
implements the E-field wave operator directly (ie, as a list of OpenCL
instructions rather than a matrix). Additionally, there is a slower
(and slightly more versatile) solver in ```csr.py``` which attempts to solve
(and slightly more versatile) solver in `csr.py` which attempts to solve
an arbitrary sparse matrix in compressed sparse row (CSR) format using
the same conjugate gradient method as the default solver. The CSR solver
is significantly slower, but can be very useful for testing alternative
@ -49,14 +49,14 @@ pip install git+https://mpxd.net/code/jan/opencl_fdfd.git@release
## Use
See the documentation for ```opencl_fdfd.cg_solver(...)```
See the documentation for `opencl_fdfd.cg_solver(...)`
(located in ```main.py```) for details about how to call the solver.
The FDFD arguments are identical to those in
```fdfd_tools.solvers.generic(...)```, and a few solver-specific
`meanas.solvers.generic(...)`, and a few solver-specific
arguments are available.
An alternate (slower) FDFD solver and a general gpu-based sparse matrix
solver is available in ```csr.py```. These aren't particularly
solver is available in `csr.py`. These aren't particularly
well-optimized, and something like
[MAGMA](http://icl.cs.utk.edu/magma/index.html) would probably be a
better choice if you absolutely need to solve arbitrary sparse matrices