GPU stack 1/8: update feectools (device ghost exchange, single-reduction PCG); pcg_sr solver option

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Part 1 of 8 of the split of #772 (cuda-aware-mpi-fixes) into stacked PRs. Requires struphy-hub/feectools#104 to be merged into feectools devel-tiny first (PR 1 bumps the submodule).

Merge struphy-hub/feectools#104 (feectools fix-cuda-aware-mpi-issues into devel-tiny) first. This PR points the feectools submodule at that branch (commit 1d8d47c).

• Submodule update: device ghost-exchange plans, fused block exchanges, PConjugateGradientSingleReduction, faster stencil_dot_3d on the GPU (details in the feectools PR).
• pcg_sr is accepted wherever pcg is (LiteralOptions.OptsSymmSolver), also with a preconditioner: Poisson, ImplicitDiffusion, GyrokineticPoissonSolve, CurlCurlSolve, VariationalDensityEvolve, VariationalMomentumAdvection. Same iterates as pcg, one global reduction per iteration instead of two.

Tests

Local, macOS without a GPU, in a fresh environment with feectools 1d8d47c and the pinned cunumpy, after merging devel (with #774 and #775). The PR passes test_cuda_parity, test_cuda_emulation, test_kernel_backends, test_sorting, test_accum_matrix_cupy, test_preconditioner_cupy, test_poisson and test_output on its own. The top of the stack also passes the mass-matrix, preconditioner, Derham-GPU, fused-gradient, Kronecker-block, Poisson, shear Alfvén, post-processing, polar fake-CuPy and all pic tests (1477 passed), the examples test for the two profiling cases, the sorting, Poisson and fused-gradient tests under mpirun -n 2, and the device MPI sort on the fake CuPy on 2 and 4 ranks. The Kronecker products match the stencil mass matrices to 5e-16 for M0, M1, M2, M3, Mv, M1n and M2n on a Cuboid, periodic and Dirichlet, on 1 and 2 ranks.
Not tested on a GPU here. The CUDA kernels and the device paths need a run on the cluster.

Stack (merge in order)

0. Device ghost-exchange plans, fused block exchanges, single-reduction PCG (CUDA-aware MPI) feectools#104 (feectools, into devel-tiny)

#	PR	base
1	#782 update feectools (device ghost exchange, single-reduction PCG); pcg_sr solver option (this PR)	devel
2	#783 host/device conversions in post-processing; math.sqrt in Species	#782
3	#784 CUDA mass-matrix assembly kernel kernel_3d_mat	#783
4	#785 apply separable mass matrices as Kronecker products of 1D banded matrices	#784
5	#786 Poisson/diffusion solve with fewer passes over the vectors	#785
6	#787 marker rows prepared inside the push kernels	#786
7	#788 chunked marker loading, row-based weight update, leaner MPI sorting; static field in PushVxB	#787
8	#789 profiling cases Poisson cube and Vlasov slab (CPU node vs GPU, GPU scaling)	#788

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