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Jukka Aho
81f4f85f3e
Implements working GPU-accelerated nodal assembly with MPI domain decomposition: - Matrix-free matvec operation on GPU (y = A*x without assembling A) - 2-6× speedup vs CPU multi-threading (114-302 Mnodes/s) - Scales to 343K nodes / 1M DOFs with acceptable communication overhead - CSR format for GPU-friendly node-to-elements connectivity - Global-to-local index remapping for partition consistency Key components: - benchmarks/multigpu_mpi_benchmark.jl: Full MPI+CUDA implementation (555 lines) - benchmarks/multigpu_results_2025-11-09.md: Detailed performance analysis - docs/book/gpu_benchmark_milestone.md: Comprehensive tutorial documentation Performance results (NVIDIA RTX A2000 12GB, 2 MPI ranks): - 30³ mesh: 114.84 Mnodes/s, 29% communication overhead - 50³ mesh: 130.64 Mnodes/s, 61% communication overhead - 70³ mesh: 301.83 Mnodes/s, 51% communication overhead Architecture validated: Nodal assembly + matrix-free + GPU = fast and scalable. Foundation complete for production FEM solver (needs: real stiffness, GMRES, preconditioner).