Jan's OpenCL FDTD electromagnetic simulation in 3 dimensions

Go to file

Jan Petykiewicz a37df3a74f expand gitignores		2019-07-15 00:06:43 -07:00
opencl_fdtd	Update parameter descriptions	2018-11-30 01:03:20 -08:00
.gitignore	expand gitignores	2019-07-15 00:06:43 -07:00
fdtd.py	Update example with bloch fields	2018-11-30 01:04:00 -08:00
LICENSE.md	Use markdown for license	2016-04-13 03:57:09 -07:00
pcgen.py	Fix triangular lattice code in pgcgen	2016-06-21 18:25:23 -07:00
README.md	move code to new location	2018-01-15 22:36:40 -08:00
requirements.txt	move code to new location	2018-01-15 22:36:40 -08:00
setup.py	Use readme as long_description	2018-09-16 20:12:52 -07:00

opencl_fdtd

opencl_fdtd is a python application for running 3D time-domain 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 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 3 minutes on my laptop.

Capabilities are currently pretty minimal:

Absorbing boundaries (CPML)
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[ind] += sin(f0 * t), or save any portion of a field to a file)

Installation

Requirements:

Optional (used for examples):

To get the code, just clone this repository:

git clone https://mpxd.net/code/jan/opencl_fdtd.git

You can install the requirements and their dependencies easily with

pip install -r requirements.txt

The root directory contains fdtd.py, which sets up and runs a sample simulation (cavity ringdown).

python3 fdtd.py