Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/bbn-q/macrospin_gpu

Macrospin simulations using PyOpenCL for GPU paralellization
https://github.com/bbn-q/macrospin_gpu

gpu macrospin pyopencl

Last synced: 8 days ago
JSON representation

Macrospin simulations using PyOpenCL for GPU paralellization

Awesome Lists containing this project

README 

        
# Macrospin-GPU



![macrospin_gpu](doc/COST-M-Vis.png)



Use PyOpenCL to run GPU code over many realizations of the Weiner process. A

convenient Jinja2-based templating system is used to allow easy specification of

physical geometry, magnetic properties, arbitrarily many spin-torque terms, and

more.



# Dependencies



* [PyOpenCL](http://mathema.tician.de/software/pyopencl/) for computation

* [PyOpenGL](http://pyopengl.sourceforge.net/) for visualization

* [tdqm](https://github.com/noamraph/tqdm) for progress bar

* [jinja2](http://jinja.pocoo.org/docs/dev/) templating GPU kernels



# Installation



Installing `macrospin_gpu` itself is quite simple. It's best to ensure that

PyOpenCL is properly installed (as described below) before continuing. At that

point you should simply be able to run:



```shell

git clone [email protected]:BBN-Q/macrospin_gpu.git

cd macrospin_gpu

pip install -e .

```



Try out some of the examples in `scripts/` to get started. Eventually I'll add

some legitimate documentation, but until that point the examples should be sufficient.

OpenGL visualizations can be seen in the `scripts/costm-visualization.py` script.



## OS X

Installing PyOpenCL with pip can be unreliable. It is best to clone the github

repository and work from there. Instead of working from the lastest and greatest

version you may want to check out a recently tagged release:



```shell

git clone [email protected]:pyopencl/pyopencl.git

cd pyopencl

git checkout v2016.2.1

python configure.py

make -j4

make install

```

In more recent builds of PyOpenCL, OpenGL interoperation should come for free.

Older versions required configuring with the `--cl-enable-gl` option.



It may be possible to use PyOpenCL from Anaconda, but I have not had a chance to

test this path.



## Windows

Use the Anaconda python distribution.



## Linux



PyOpenCL is not available from Anaconda so there is a bit more configuration to

be done on Linux.



### NVIDIA Drivers with Prime



Tested on Linux Mint 18.1 with nvidia 378 drivers.  Have installed following

packages: `nvidia-378`, `nvidia-opencl-icd-378`, `nvida-settings`,

`nvidia-prime` and `nvidia-modprobe-361`  for NVIDIA support and the generic

`opencl-headers`, `ocl-icd-libopencl1` and `ocl-icd-opencl-dev` for building

OpenCL program and `clinfo` to see if anything works. Need to have Nvidia card

powered up using Prime.



### Build and install PyOpenCL



Again, manually building is recommended. On modern Linux distributions when

using Anaconda Python there may be a conflict between the system `libstdc++` and

the one Anaconda ship. If you see errors with "undefined symbols" when trying to

import `pyopencl`, you may have to using Anaconda gcc to build PyOpenCL or

rename the Anaconda `libstdc++`. See this [SO

answer](http://stackoverflow.com/a/43244137/5445278) for details.



```shell

git clone [email protected]:pyopencl/pyopencl.git

cd pyopencl

git checkout v2016.2.1

./configure.py

make -j4

make install

```



## Funding



This software is based in part upon work supported by the Office of the Director

of National Intelligence (ODNI), Intelligence Advanced Research Projects

Activity (IARPA), via contract W911NF-14-C0089. The views and conclusions

contained herein are those of the authors and should not be interpreted as

necessarily representing the official policies or endorsements, either expressed

or implied, of the ODNI, IARPA, or the U.S. Government.