PetaVision is an open source, object oriented neural simulation toolbox optimized for high-performance multi-core, multi-node computer architectures. PetaVision 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.
Petavision has been used on a range of vision and learning tasks including depth inference, action classification, and learning from multiple intelligence streams including weather and commodity prices. PetaVision has been used to perform image classification, sound analysis, and image-rescaling and is flexible enough to grow with your imagination.
Installation instructions can be found on our documentation page. Jump over to our wiki tutorial page to get started with a basic example of running PetaVision. Our code is documented using doxygen.
If you have an account on Amazon Web Services, you can try PetaVision using our public AMI on aws.amazon.com. Search for "PetaVision Public AMI" and start an instance. Use a GPU instance (e.g. g2.8xlarge) to take full advantage of PetaVision's acceleration toolkit. Follow the instructions in our documentation for AWS to get started.