If you've completed all the previous steps to get CUDA working, then using CUDA is a fairly simple affair. You simply need to compile your application with the following:

go build -tags='cuda'

This builds your executable with CUDA support and uses CUDA, rather than the CPU, to run your deep learning model.

To illustrate, let's use an example we're already familiar with – a neural network with weights:

w0 := gorgonia.NewMatrix(g, dt, gorgonia.WithShape(784, 300), gorgonia.WithName("w0"), gorgonia.WithInit(gorgonia.GlorotN(1.0)))

w1 := gorgonia.NewMatrix(g, dt, gorgonia.WithShape(300, 100), gorgonia.WithName("w1"), gorgonia.WithInit(gorgonia.GlorotN(1.0)))

w2 := gorgonia.NewMatrix(g, dt, gorgonia.WithShape(100, 10), gorgonia.WithName("w2"), gorgonia.WithInit(gorgonia.GlorotN(1.0)))

This is just our simple feedforward neural network that we built to use on the MNIST dataset.