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GPU stack 3/8: CUDA mass-matrix assembly kernel kernel_3d_mat - #784
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- kernel_3d_mat_cuda.cu: one thread per (element, codomain basis function, domain basis function); replaces the host fallback on the CuPy backend. - WeightedMassOperator.assemble reads the quadrature grids (spans, weights, basis values) as backend arrays, copied to the device once and cached. - Simulation.allocate compiles the assembly kernel before it is first called, so the compilation is not counted in the assembly's profiling regions. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Random quadrature data on 3 x 2 x 2 elements with mixed degrees, with the first row local or a ghost row. test_cuda_kernels_have_parity_cases requires a case for every kernel with a CUDA version; the emulation test compares it with the pyccel kernel without a GPU. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This was referenced Oct 16, 2026
max-models
added this pull request to stack #790
October 16, 2026 08:51
…(feectools update)
…(feectools update)
…(pcg_sr in the shear Alfven solves)
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Part 3 of 8 of the split of #772 (
cuda-aware-mpi-fixes) into stacked PRs. Requires struphy-hub/feectools#104 to be merged into feectoolsdevel-tinyfirst (PR 1 bumps the submodule).kernel_3d_mat_cuda.cu: one thread per (element, codomain basis function, domain basis function). It replaces the host fallback on the CuPy backend (missing_cuda="fallback"removed, launch size fromn_threads_from).WeightedMassOperator.assemblereads the quadrature grids (spans, weights, basis values) as backend arrays, copied to the device once and cached.Simulation.allocatecompiles the assembly kernel before the first assembly, in its own profiling region (setup: compile cuda kernels (assembly)), so the ~1 s compilation is not counted in the assembly.Added while splitting: parity cases for
kernel_3d_mat(random quadrature data on 3×2×2 elements with mixed degrees, with and without a ghost row).test_cuda_kernels_have_parity_casesrequires one for every kernel with a CUDA version. The emulation test confirms that the CUDA kernel matches the pyccel kernel without a GPU.Tests
Local, macOS without a GPU, in a fresh environment with feectools
1d8d47cand the pinned cunumpy, after merging devel (with #774 and #775). The PR passestest_cuda_parity,test_cuda_emulation,test_kernel_backends,test_sorting,test_accum_matrix_cupy,test_preconditioner_cupy,test_poissonandtest_outputon 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 allpictests (1477 passed), the examples test for the two profiling cases, the sorting, Poisson and fused-gradient tests undermpirun -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)
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