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What is OpenPV?
OpenPV is an open source, object oriented neural simulation toolbox optimized for high-performance multi-core, multi-node computer architectures. OpenPV is intended for computational neuroscientists who seek to apply neuromorphic models to hard signal processing problems both to improve on the performance of existing algorithms and/or to gain insight into the computational mechanisms underlying biological neural processing.
How do I get started?
Start by downloading the OpenPV source code from GitHub along with any necessary 3rd party packages. Follow the detailed instructions in our documentation
Are there any recommended systems for running OpenPV?
We have successfully built OpenPV on many *nix operating systems, however, we do recommend that you set up on a linux machine if possible. In order to run on OS X with OpenMP parallelism, you will need a more recent version of Clang than is supplied by Apple Xcode currently (Sep 14, 2015). See the OS X installation page for details.
I want to use the OpenPV code base and develop new applications. How do I do that?
OpenPV is licensed by the Eclipse Public License and you can review the terms here. We encourage new users to try to install OpenPV on their own machines and to feel free to develop new sub-classes and functions into OpenPV. Please make sure to cite OpenPV in your code.
What is the meaning behind the logo?
The logo has a couple of interpretations. The first intended meaning was to create a minimalistic represetation of a standard experiment set-up in OpenPV: a V1 LCA. This consists of a image layer that points to an error layer, that points to the sparse V1 layer that points back to the error layer. If V1 has found an excellent sparse represenation of the image, only a few elements should be active (the white blocks in the top layer). Another intended meaning was to capture the scenic beauty of the valleys and peaks around Los Alamos, New Mexico during the night.
My question wasn't addressed here. What now?
The developers of OpenPV can be contacted via the e-mail link found on the sidebar titled "Questions?". Similarly, if you have discovered a bug in the code base (we assure you that we have hidden plenty in there for you), feel free to create a GitHub Issue with relevant information.