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Neurokernel is a Python framework for developing models of the fruit fly brain and executing them on multiple NVIDIA GPUs.
Neurokernel requires
- Linux (other operating systems may work, but have not been tested);
- Python 2.7 (Python 3.0 is not guaranteed to work);
- at least one NVIDIA GPU with Fermi architecture or later;
- NVIDIA's GPU drivers;
- CUDA 5.0 or later;
- OpenMPI 1.8.4 or later compiled with CUDA support.
To check what GPUs are in your system, you can use the inxi command available on most Linux distributions:
inxi -G
You can verify that the drivers are loaded as follows:
lsmod | grep nvidia
If no drivers are present, you may have to manually load them by running something like:
modprobe nvidia
as root.
Although some Linux distributions do include CUDA in their stock package repositories, you are encouraged to use those distributed by NVIDIA because they often are more up-to-date and include more recent releases of the GPU drivers. See this page for download information.
If you install Neurokernel in a virtualenv environment, you will need to install OpenMPI. See this page for OpenMPI installation information. Note that OpenMPI 1.8 cannot run on Windows.
Some of Neurokernel's demos require either ffmpeg or libav installed to generate visualizations (see Examples).
Download the latest Neurokernel code as follows:
git clone https://github.com/neurokernel/neurokernel.git
Since Neurokernel requires a fair number of additional Python packages to run, it is recommended that it either be installed in a virtualenv or conda environment. Follow the relevant instructions below.
See this page for virtualenv installation information.
Create a new virtualenv environment and install several required dependencies:
cd ~/ virtualenv NK ~/NK/bin/pip install numpy cython numexpr pycuda
If installation of PyCUDA fails because some of the CUDA development files or
libraries are not found, you may need to specify where they are explicitly. For
example, if CUDA is installed in /usr/local/cuda/, try installing PyCUDA
as follows:
CUDA_ROOT=/usr/local/cuda/ CFLAGS=-I${CUDA_ROOT}/include \
LDFLAGS=-L${CUDA_ROOT}/lib64 ~/NK/bin/pip install pycuda
Replace ${CUDA_ROOT}/lib with ${CUDA_ROOT}/lib64 if your system is
running 64-bit Linux. If you continue to encounter installation problems, see
the PyCUDA Wiki for more information.
Run the following to install the remaining Python package dependencies listed in setup.py:
cd ~/neurokernel ~/NK/bin/python setup.py develop
Note that conda packages are currently only available for 64-bit Ubuntu Linux 14.04. If you would like packages for another distribution, please submit a request to the Neurokernel developers.
First, install the following Ubuntu packages:
libibverbs1libnuma1libpmi0libslurm26libtorque2
These are required by the conda OpenMPI packages prepared
for Neurokernel. Ensure that the stock Ubuntu OpenMPI packages are not installed
because they may interfere with the ones that will be installed by conda. You
also need to ensure that CUDA has been installed in
/usr/local/cuda.
Install conda by either installing Anaconda or Miniconda. Make sure that the following lines appear in your ~/.condarc file so that conda can find the packages required by Neurokernel:
channels: - https://conda.binstar.org/neurokernel/channel/ubuntu1404 - defaults
Create a new conda environment containing the packages required by Neurokernel by running the following command:
conda create -n NK neurokernel_deps
PyCUDA packages compiled against several versions of CUDA are available. If you
need one compiled against a specific version that differs from the one
automatically installed by the above command, you will need to manually install
it afterwards as follows (replace cuda75 with the appropriate version):
source activate NK conda install pycuda=2015.1.3=np110py27_cuda75_0 source deactivate
Activate the new environment and install Neurokernel in it as follows:
source activate NK cd ~/neurokernel python setup.py develop
Introductory examples of how to use Neurokernel to build and integrate models of different parts of the fly brain are available in the Neurodriver package. To install it run the following:
git clone https://github.com/neurokernel/neurodriver cd ~/neurodriver python setup.py develop
Other models built using Neurokernel are available on GitHub.
To build Neurokernel's HTML documentation locally, you will need to install
- mock 1.0 or later.
- sphinx 1.3 or later.
- sphinx_rtd_theme 0.1.6 or later.
Once these are installed, run the following:
cd ~/neurokernel/docs make html
See the included AUTHORS file for more information.
This software is licensed under the BSD License. See the included LICENSE file for more information.
The Neurokernel Project is independent of the NeuroKernel Operating System developed by NeuroDNA Computer.