Nengo OpenCL 1.1 released

The Nengo OCL team is delighted to announce the release of Nengo OpenCL 1.1.

What is Nengo OpenCL?

Nengo OpenCL is a backend for Nengo that uses the OpenCL framework to run large-scale neural models on CPUs, GPUs, and other OpenCL-capable platforms. Using the OpenCL backend can be orders of magnitude faster than the reference backend for large models.

How do I use it?

To use Nengo OpenCL, replace instances of nengo.Simulator with nengo_ocl.Simulator.

For example, if you have a network called model and you run it with

with nengo.Simulator(model) as sim:

you would change that to

with nengo_ocl.Simulator(model) as sim:

and that’s it!

What’s new?

Nengo OpenCL 1.1.0 adds support for several Nengo features, including RectifiedLinear and Sigmoid neuron types, arbitrary Process subclasses, and filtering matrices.

This version of Nengo OpenCL also improves compatibility with Nengo, NumPy, and Python 3. Nengo OpenCL works on Python 2.7 and 3.4+, with Nengo version 2.1.2 and later, including the newly released 2.3.0.

To see the full list of changes in Nengo OpenCL 1.1, head to the Github release page.

How do I get it?

Installing Nengo OpenCL is more difficult than other parts of the Nengo ecosystem since OpenCL must be properly installed first. See our notes on installing OpenCL for assistance.

Once OpenCL is installed, use pip.

pip install --upgrade nengo_ocl

If something goes wrong during the installation, which can happen due to differing OpenCL installs, refer to our installation notes for assistance.

Where can I learn more?

Where can I get help?

Please come to the Nengo forum! We welcome any questions and suggestions you might have.