Define LU factorization for JLArray

[ChrisRackauckas-Claude]

Ignore this PR until reviewed by @ChrisRackauckas.\n\n## Summary\n\nJLArrays now defines LinearAlgebra.lu for JLArray matrices by explicitly copying to the host representation before calling host LU. Matching ldiv! methods copy right-hand sides through host memory so the returned factorization can be used by solver code without triggering JLArray to Ptr conversion.\n\nThis addresses the regression described in SciML/OrdinaryDiffEq.jl#4179. JLArrays 0.3.2 intentionally rejects implicit CPU pointer conversion, while the generic LinearAlgebra LU path still reaches LAPACK with a JLArray.\n\n## Verification\n\nBefore the fix, on the unmodified branch:\n\n julia --project=test --startup-file=no -e 'using JLArrays, LinearAlgebra; A = jl([2.0 1.0; 1.0 3.0]); lu(A; check = false)'\n\nfailed with:\n\n ERROR: Illegal conversion of a JLArray to a Ptr\n [3] getrf!(A::JLArray{Float64, 2}, ipiv::JLArray{Int64, 1}; check::Bool)\n @ LinearAlgebra.LAPACK .../LinearAlgebra/src/lapack.jl:587\n\nWith this patch:\n\n julia --project=test --startup-file=no test/jlarrays_lu.jl\n\npassed:\n\n Test Summary: | Pass Total Time\n JLArray LU | 3 3 1.3s\n\nThe OrdinaryDiffEq reproduction also passed for both TRBDF2 and Rodas5P:\n\n (SciMLBase.ReturnCode.Success, SciMLBase.ReturnCode.Success, [0.04713496106370036, 0.04713496106370036, 0.04713496106370036])\n\nThe full GPUArrays suite passed:\n\n Test Summary: | Pass Total Time\n Overall | 21022 21022 16m23.0s\n SUCCESS\n Testing GPUArrays tests passed\n\nAlso ran typos on the changed files and git diff --check. GPU-specific backends and downstream packages were not tested.

[ChrisRackauckas]

It was effectively doing this before the pointer conversion was removed

[kshyatt]

Brother what is this PR description

[ChrisRackauckas]

ehh have your llm summarize it.