acceleration_and_parallelism.md

Acceleration and Parallelism

!!! warning "Experimental API"

The acceleration API is experimental and may not work correctly in all
cases, especially if trying to use an acceleration method that your
version of Julia or installed packages cannot support. The API is also
subject to breaking changes during minor or major releases without
warning.

User-facing interface

To enable composable, extensible acceleration of core MLJ methods, ComputationalResources.jl is utilized to provide some basic types and functions to make implementing acceleration easy. However, ambitious users or package authors have the option to define their own types to be passed as resources to acceleration, which must be <:ComputationalResources.AbstractResource.

Methods which support some form of acceleration support the acceleration keyword argument, which can be passed a "resource" from ComputationalResources. For example, passing acceleration=CPUProcesses() will utilize Distributed's multiprocessing functionality to accelerate the computation, while acceleration=CPUThreads() will use Julia's PARTR threading model to perform acceleration.

The default computational resource is CPU1(), which is simply serial processing via CPU. The default resource can be changed as in this example: MLJ.default_resource(CPUProcesses()). The argument must always have type <:ComputationalResource.AbstractResource. To inspect the current default, use MLJ.default_resource().

!!! note

The `CPUThreads()` resource is only available when running a version of
Julia with `Threads.@spawn` available.

!!! note

You cannot use `CPUThreads()` with models wrapping python code.