Automatic Differentiation Backends

Note

We support all backends supported by DifferentiationInterface.jl. Please refer to the backends page for more information.

Summary of Finite Differencing Backends

AutoFiniteDiff: Finite differencing using FiniteDiff.jl, not optimal but always applicable.
AutoFiniteDifferences: Finite differencing using FiniteDifferences.jl, not optimal but always applicable.

Summary of Forward Mode AD Backends

AutoForwardDiff: The best choice for dense problems.
AutoPolyesterForwardDiff: Might be faster than AutoForwardDiff for large problems. Requires PolyesterForwardDiff.jl to be installed and loaded.

Summary of Reverse Mode AD Backends

AutoZygote: The fastest choice for non-mutating array-based (BLAS) functions.
AutoEnzyme: Uses Enzyme.jl Reverse Mode and works for both in-place and out-of-place functions.

Tip

For sparsity detection and sparse AD take a look at sparsity detection.