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GPU Management

Info

Starting from v0.5, Lux has transitioned to a new GPU management system. The old system using cpu and gpu functions is still in place but will be removed in v1. Using the old functions might lead to performance regressions if used inside performance critical code.

Lux.jl can handle multiple GPU backends. Currently, the following backends are supported:

julia
# Important to load trigger packages
using Lux, LuxCUDA #, AMDGPU, Metal, oneAPI

supported_gpu_backends()
("CUDA", "AMDGPU", "Metal", "oneAPI")

Metal Support

Support for Metal GPUs should be considered extremely experimental at this point.

Automatic Backend Management (Recommended Approach)

Automatic Backend Management is done by two simple functions: cpu_device and gpu_device.

  • cpu_device: This is a simple function and just returns a CPUDevice object. @example gpu_management cdev = cpu_device()@example gpu_management x_cpu = randn(Float32, 3, 2)

  • gpu_device: This function performs automatic GPU device selection and returns an object.

    1. If no GPU is available, it returns a CPUDevice object.

    2. If a LocalPreferences file is present, then the backend specified in the file is used. To set a backend, use Lux.gpu_backend!(<backend_name>). (a) If the trigger package corresponding to the device is not loaded, then a warning is displayed. (b) If no LocalPreferences file is present, then the first working GPU with loaded trigger package is used.

    @example
    x_gpu = x_cpu |&gt; gdev  ```
    `@example gpu_management  (x_gpu |> cdev) ≈ x_cpu`

Manual Backend Management

Automatic Device Selection can be circumvented by directly using CPUDevice and AbstractGPUDevice objects.

julia
cdev = cpu_device()

x_cpu = randn(Float32, 3, 2)

if MLDataDevices.functional(CUDADevice)
    gdev = CUDADevice()
    x_gpu = x_cpu |> gdev
elseif MLDataDevices.functional(AMDGPUDevice)
    gdev = AMDGPUDevice()
    x_gpu = x_cpu |> gdev
else
    @info "No GPU is available. Using CPU."
    x_gpu = x_cpu
end

(x_gpu |> cdev)  x_cpu
true