Make `num_vecjac<!>` GPU compatible

[vpuri3]

SparseDiffTools.jl/src/differentiation/vecjac_products.jl

Lines 24 to 29 in 9a713c6

	for i in 1:length(x)
	x[i] += ϵ
	f0 = f(x)
	x[i] -= ϵ
	du[i] = (((f0 .- _f0) ./ ϵ)' * vv)[1]
	end

[ChrisRackauckas]

The autodiff ones should be GPU compatible already at least? Those ones should be tested on CI too. The numerical differentiation ones need some separate dispatches.

[vpuri3]

Auto-diff ones work on GPU. num_jacvec<!> looks GPU compatible as well. From a cursory look num_vecjac<!> look like only ones that aren't.

[vpuri3]

@ChrisRackauckas any idea how we can make this GPU? Can we use LinearAlgebra functions or does it need its own CUDA kernel?

[ChrisRackauckas]

Look at how FintieDiff.jl was made GPU compatible. You need to locally force allowscalar and it's a bit slow, and that's kind of required.