I am wondering how much work it would be to make QN operators compatible with GPUs (CuArray for instance)? Typically, my use case would be something like this ``` using CUDA, NLPModels, NLPModelsModifiers, NLPModelsTest V = CuArray{Float64} nlp = NLSLC(V) CUDA.allowscalar() list_QN = [LBFGSModel, LSR1Model, DiagonalPSBModel, DiagonalAndreiModel, SpectralGradientModel] lnlp = list[1](nlp) x = nlp.meta.x0 v = copy(x) Hv = similar(x) hprod!(lnlp, x, v, Hv) ``` These model modifiers internally call the QN operators from LinearOperators.jl, e.g. `op = LBFGSOperator(T, nlp.meta.nvar)`.
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