CUDA support - #90
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* CUDA step 1: run feectools with the CuPy backend Make feectools work when cunumpy's backend is CuPy, without any device kernels yet: kernels that stay on the host still copy their arrays. - Wrap all Pyccel kernels (stencil, B-splines, field evaluation, DOF kernels) in cunumpy.PyccelKernel, so they accept CuPy arrays. - Keep host-only metadata on NumPy: MPI/index bookkeeping in ddm (cart, partition, petsc) and fem.partitioning, Kronecker solver sizes, and index arithmetic with Python ints (compute_diag_len, math.prod). - Stage data for host-only libraries by array, not by global backend: LAPACK/SuperLU direct solvers, SciPy FFT, SciPy sparse products. - Fix calls that ran host kernels on device arrays: the second stencil2coo call in StencilMatrix.tosparse and the conjugate transpose. - Vectorize the construction of the 1D collocation matrices in the global projectors (element-wise indexing was a device round trip per entry: 334 s of a 348 s Derham setup on the GPU). - GMRES: take real scalars from CuPy views before modifying them. - Fix StencilMatrix._update_ghost_regions_serial: the ghost region is pads * shifts wide (wrong whenever shifts > 1, on both backends). - Tests: work with CuPy arrays; skip PETSc tests without petsc4py. Serial tests pass on both backends (core, ddm, fem, linalg). Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * run ci --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
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