forked from jan/opencl_fdtd
54 lines
1.6 KiB
Markdown
54 lines
1.6 KiB
Markdown
# opencl_fdtd
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**opencl_fdtd** is a python application for running 3D time-domain
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electromagnetic simulations on parallel compute hardware (mainly GPUs).
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**Performance** highly depends on what hardware you have available:
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* A 395x345x73 cell simulation (~10 million points, 8-cell absorbing boundaries)
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runs at around 91 iterations/sec. on my AMD RX480.
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* On an Nvidia GTX 580, it runs at 66 iterations/sec
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* On my laptop (Nvidia 940M) the same simulation achieves ~12 iterations/sec.
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* An L3 photonic crystal cavity ringdown simulation (1550nm source, 40nm
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discretization, 8000 steps) takes about 3 minutes on my laptop.
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**Capabilities** are currently pretty minimal:
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* Absorbing boundaries (CPML)
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* Perfect electrical conductors (PECs; to use set epsilon to inf)
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* Anisotropic media (eps_xx, eps_yy, eps_zz, mu_xx, ...)
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* Direct access to fields (eg., you can trivially add a soft or hard
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current source with just sim.E[ind] += sin(f0 * t), or save any portion
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of a field to a file)
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## Installation
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**Requirements:**
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* python 3 (written and tested with 3.5)
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* numpy
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* pyopencl
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* jinja2
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* [fdfd_tools](https://mpxd.net/code/jan/fdfd_tools)
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Optional (used for examples):
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* dill (for file output)
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* [gridlock](https://mpxd.net/code/jan/gridlock)
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* [masque](https://mpxd.net/code/jan/masque)
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To get the code, just clone this repository:
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```bash
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git clone https://mpxd.net/code/jan/opencl_fdtd.git
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```
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You can install the requirements and their dependencies easily with
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```bash
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pip install -r requirements.txt
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```
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## Running
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The root directory contains ``fdtd.py``, which sets up and runs a sample simulation
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(cavity ringdown).
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```bash
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python3 fdtd.py
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```
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