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Jan Petykiewicz 2017-03-29 01:09:21 -07:00
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@ -5,28 +5,32 @@ electromagnetic simulations on parallel compute hardware (mainly GPUs).
**Performance** highly depends on what hardware you have available:
* A 395x345x73 cell simulation (~10 million points, 8-cell absorbing boundaries)
runs at around 42 iterations/sec. on my Nvidia GTX 580.
* On my laptop (Nvidia 940M) the same simulation achieves ~8 iterations/sec.
runs at around 91 iterations/sec. on my AMD RX480.
* On an Nvidia GTX 580, it runs at 66 iterations/sec
* On my laptop (Nvidia 940M) the same simulation achieves ~12 iterations/sec.
* An L3 photonic crystal cavity ringdown simulation (1550nm source, 40nm
discretization, 8000 steps) takes about 5 minutes on my laptop.
discretization, 8000 steps) takes about 3 minutes on my laptop.
**Capabilities** are currently pretty minimal:
* Absorbing boundaries (CPML)
* Conducting boundaries (PMC)
* Perfect electrical conductors (PECs; to use set epsilon to inf)
* Anisotropic media (eps_xx, eps_yy, eps_zz, mu_xx, ...)
* Direct access to fields (eg., you can trivially add a soft or hard
current source with just sim.E[1] += sin(f0 * t), or save any portion
current source with just sim.E[ind] += sin(f0 * t), or save any portion
of a field to a file)
## Installation
**Requirements:**
* python 3 (written and tested with 3.5)
* numpy
* pyopencl
* h5py (for file output)
* jinja2
* dill (for file output)
* [gridlock](https://mpxd.net/gogs/jan/gridlock)
* [masque](https://mpxd.net/gogs/jan/masque)
* [fdfd_tools](https://mpxd.net/gogs/jan/fdfd_tools)
To get the code, just clone this repository:
```bash