mirror of
https://github.com/JuliaFEM/JuliaFEM.jl.git
synced 2026-08-29 07:32:54 +00:00
Jukka Aho
309 lines
11 KiB
Julia
309 lines
11 KiB
Julia
# This file is a part of JuliaFEM.
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# License is MIT: see https://github.com/JuliaFEM/JuliaFEM.jl/blob/master/LICENSE.md
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"""
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Regression + correctness tests for `apply_K!` — the matrix-free `y = K x`
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sibling of `assemble!` on the DOF-based assembler.
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For every problem size:
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1. Build assembled `K` via `assemble!` + `extract_system`.
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2. Build the same `y_ref = K * x_random` for several random `x`.
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3. Compare against `y_mf` from `apply_K!(y_mf, …, x)`. Must agree to
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round-off (no accumulation difference: same DOF traversal, same
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evaluate_entry inside).
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4. Assert `apply_K!` is zero-allocation after warmup.
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5. Assert the optimized LLVM IR for `apply_K!` has 0 GC allocation
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sites — guarantees the inner accumulate loop never heap-allocates,
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which is the whole point of the matrix-free path for Krylov.
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"""
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using Test
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using JuliaFEM
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using JuliaFEM: DOFBasedCOOAssembler, DOFBasedCOOCache, apply_K!
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using JuliaFEM: create_elements!, @DOFSet, DOF, Displacement, Vertex
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using LinearAlgebra
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using SparseArrays
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using Tensors
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using Random
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using InteractiveUtils # code_llvm
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using LinearOperators # LinearOperator wrapper for apply_K!
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using IterativeSolvers # cg
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# ----------------------------------------------------------------------------
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# Mesh helpers (shared shape with test_dof_based_zero_alloc.jl, kept local
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# so the two regression tests stay independent).
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# ----------------------------------------------------------------------------
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function _build_hex8_box(nx::Int, ny::Int, nz::Int)
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nodes = Vec{3,Float64}[]
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nidx(i, j, k) = (i - 1) + (j - 1) * (nx + 1) + (k - 1) * (nx + 1) * (ny + 1) + 1
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for k in 1:(nz + 1), j in 1:(ny + 1), i in 1:(nx + 1)
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push!(nodes, Vec{3}((Float64(i - 1) / nx,
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Float64(j - 1) / ny,
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Float64(k - 1) / nz)))
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end
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conns = NTuple{8,UInt32}[]
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for k in 1:nz, j in 1:ny, i in 1:nx
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n1 = nidx(i, j, k)
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n2 = nidx(i + 1, j, k)
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n3 = nidx(i + 1, j + 1, k)
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n4 = nidx(i, j + 1, k)
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n5 = nidx(i, j, k + 1)
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n6 = nidx(i + 1, j, k + 1)
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n7 = nidx(i + 1, j + 1, k + 1)
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n8 = nidx(i, j + 1, k + 1)
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push!(conns, (UInt32(n1), UInt32(n2), UInt32(n3), UInt32(n4),
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UInt32(n5), UInt32(n6), UInt32(n7), UInt32(n8)))
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end
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return Mesh{8,Hexahedron{8}}(nodes, conns)
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end
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function _build_single_tet4()
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nodes = Vec{3,Float64}[
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Vec{3}((0.0, 0.0, 0.0)),
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Vec{3}((1.0, 0.0, 0.0)),
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Vec{3}((0.5, 1.0, 0.0)),
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Vec{3}((0.5, 0.5, 1.0)),
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]
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conns = [(UInt32(1), UInt32(2), UInt32(3), UInt32(4))]
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return Mesh{Tetrahedron{4}}(nodes, conns)
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end
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"Set up DOF-based cache + kernel for elasticity."
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function _setup(mesh, ::Type{Topo}) where {Topo}
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material = LinearElastic(E = 210e9, ν = 0.3)
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kernel = ContinuumKernel(ContinuumFormulation{FullThreeD}(),
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material, Displacement{3}())
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S = @DOFSet{u::DOF{Displacement{3}, Vertex}}
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elements, dof_mgr = create_elements!(mesh, Element{Topo, Lagrange{1}, S})
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asm = DOFBasedCOOAssembler()
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cache = DOFBasedCOOCache(elements, dof_mgr, mesh, kernel)
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return cache, asm, kernel, mesh
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end
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# ----------------------------------------------------------------------------
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# Tests
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# ----------------------------------------------------------------------------
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@testset "apply_K!: correctness vs assembled K" begin
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println("\n" * "=" ^ 70)
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println("DOF-BASED APPLY_K! CORRECTNESS")
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println("=" ^ 70)
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Random.seed!(20260508)
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# ------------------------------------------------------------------
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# 1. Single Tet4
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# ------------------------------------------------------------------
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@testset "Single Tet4" begin
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mesh = _build_single_tet4()
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cache, asm, kernel, m = _setup(mesh, Tetrahedron{4})
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# Assemble K once; compare K*x against apply_K!(y, …, x) for
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# several random x.
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assemble!(cache, asm, kernel, m)
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K, _ = extract_system(cache)
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n = size(K, 1)
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max_rel = 0.0
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for trial in 1:8
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x = randn(n)
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y_ref = K * x
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y_mf = zeros(n)
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apply_K!(y_mf, cache, asm, kernel, m, x)
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rel = norm(y_mf - y_ref) / max(norm(y_ref), 1.0)
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@test rel < 1e-12
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max_rel = max(max_rel, rel)
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end
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println(" Single Tet4 ...... n=$n max rel=$(round(max_rel; sigdigits=3))")
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end
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# ------------------------------------------------------------------
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# 2. Growing Hex8 cube meshes
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# ------------------------------------------------------------------
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@testset "Hex8 cube $(nx)×$(ny)×$(nz)" for (nx, ny, nz) in
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[(1, 1, 1), (2, 1, 1), (4, 2, 2), (6, 3, 3), (8, 4, 4)]
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mesh = _build_hex8_box(nx, ny, nz)
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cache, asm, kernel, m = _setup(mesh, Hexahedron{8})
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assemble!(cache, asm, kernel, m)
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K, _ = extract_system(cache)
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n = size(K, 1)
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max_rel = 0.0
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for trial in 1:5
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x = randn(n)
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y_ref = K * x
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y_mf = zeros(n)
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apply_K!(y_mf, cache, asm, kernel, m, x)
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rel = norm(y_mf - y_ref) / max(norm(y_ref), 1.0)
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@test rel < 1e-12
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max_rel = max(max_rel, rel)
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end
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nelems = length(m.connectivity)
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println(" Hex8 $(nx)×$(ny)×$(nz) $(lpad(nelems, 5)) elem " *
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"$(lpad(n, 5)) dof max rel=$(round(max_rel; sigdigits=3))")
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end
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end
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# ----------------------------------------------------------------------------
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# Zero-allocation + LLVM IR check for apply_K!
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# ----------------------------------------------------------------------------
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@testset "apply_K!: zero allocation + 0 LLVM gc-alloc sites" begin
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println("\n" * "=" ^ 70)
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println("DOF-BASED APPLY_K! ZERO-ALLOC")
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println("=" ^ 70)
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@testset "Single Tet4" begin
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mesh = _build_single_tet4()
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cache, asm, kernel, m = _setup(mesh, Tetrahedron{4})
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n = cache.ndofs
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x = ones(n)
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y = zeros(n)
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# Warmup: compile + populate caches
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apply_K!(y, cache, asm, kernel, m, x)
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GC.gc()
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a = @allocated apply_K!(y, cache, asm, kernel, m, x)
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@test a == 0
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println(" Single Tet4 ........................ allocs=$a")
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end
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@testset "Hex8 cube $(nx)×$(ny)×$(nz)" for (nx, ny, nz) in
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[(1, 1, 1), (2, 1, 1), (4, 2, 2), (6, 3, 3), (8, 4, 4)]
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mesh = _build_hex8_box(nx, ny, nz)
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cache, asm, kernel, m = _setup(mesh, Hexahedron{8})
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n = cache.ndofs
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x = ones(n)
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y = zeros(n)
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apply_K!(y, cache, asm, kernel, m, x) # warmup
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GC.gc()
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a = @allocated apply_K!(y, cache, asm, kernel, m, x)
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@test a == 0
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nelems = length(m.connectivity)
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println(" Hex8 $(nx)×$(ny)×$(nz) $(lpad(nelems,5)) elem " *
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"$(lpad(n,5)) dof allocs=$a")
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end
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@testset "Optimized LLVM IR has 0 gc-alloc sites" begin
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mesh = _build_hex8_box(2, 1, 1)
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cache, asm, kernel, m = _setup(mesh, Hexahedron{8})
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n = cache.ndofs
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x = ones(n)
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y = zeros(n)
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apply_K!(y, cache, asm, kernel, m, x) # warmup
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iob = IOBuffer()
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code_llvm(iob, apply_K!,
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Tuple{typeof(y), typeof(cache), typeof(asm),
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typeof(kernel), typeof(m), typeof(x)};
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optimize = true)
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ir = String(take!(iob))
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n_alloc =
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length(collect(eachmatch(r"call.*julia\.gc_alloc", ir))) +
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length(collect(eachmatch(r"call.*jl_gc_pool_alloc", ir))) +
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length(collect(eachmatch(r"call.*jl_gc_big_alloc", ir))) +
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length(collect(eachmatch(r"call.*jl_gc_alloc_typed", ir)))
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@test n_alloc == 0
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println(" apply_K! optimized LLVM IR: $n_alloc gc-alloc sites " *
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"($(length(ir)) IR chars)")
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end
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end
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# ----------------------------------------------------------------------------
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# Krylov demo: matrix-free CG using `apply_K!` as a `LinearOperator`.
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# This is the actual use case for the matrix-free path — once it solves,
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# the API is proven end-to-end against an off-the-shelf solver.
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# ----------------------------------------------------------------------------
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@testset "apply_K!: matrix-free CG via LinearOperators + IterativeSolvers" begin
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println("\n" * "=" ^ 70)
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println("DOF-BASED APPLY_K! — KRYLOV VALIDATION")
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println("=" ^ 70)
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# Small unit cube, 3×3×3 = 27 elements, 192 DOFs.
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nx = ny = nz = 3
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mesh = _build_hex8_box(nx, ny, nz)
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cache, asm, kernel, m = _setup(mesh, Hexahedron{8})
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n = cache.ndofs
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# Bottom-face homogeneous Dirichlet via the shared `PenaltyDirichlet`
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# abstraction — same struct that the heat domain uses.
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fixed_dofs = Int[]
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for (nid, X) in enumerate(m.nodes)
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if X[3] == 0.0
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push!(fixed_dofs, 3*(nid - 1) + 1)
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push!(fixed_dofs, 3*(nid - 1) + 2)
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push!(fixed_dofs, 3*(nid - 1) + 3)
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end
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end
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@test !isempty(fixed_dofs)
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bc = PenaltyDirichlet(fixed_dofs; penalty = 1e16)
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# Loading: unit downward force on the corner (nx+1, ny+1, nz+1).
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top_corner_node = (nx + 1) * (ny + 1) * (nz + 1)
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fz_dof = 3 * (top_corner_node - 1) + 3
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b = zeros(n)
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b[fz_dof] = -1e6 # 1 MN (problem is in SI; just a number)
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# 1. Direct solution via assembled K with the same penalty BC.
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assemble!(cache, asm, kernel, m)
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K, _ = extract_system(cache)
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Kbc = Matrix(K)
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apply_constraint!(Kbc, bc)
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u_direct = Kbc \ b
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# 2. Matrix-free CG: `matrix_free_op` builds the closure with the
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# Dirichlet contribution baked in. No K is materialized.
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op = matrix_free_op(cache, asm, kernel, m; dirichlet = bc)
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linop = LinearOperator(Float64, n, n, true, true, op)
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u_mf = zeros(n)
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cg!(u_mf, linop, b; abstol = 1e-8, reltol = 1e-10, maxiter = 4 * n)
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# 3. Compare matrix-free to direct.
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rel_u = norm(u_mf - u_direct) / max(norm(u_direct), 1.0)
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@test rel_u < 1e-6
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# Also verify residual of matrix-free solution under the same operator.
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r = zeros(n)
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op(r, u_mf)
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rel_r = norm(b - r) / max(norm(b), 1.0)
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@test rel_r < 1e-6
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println(" Hex8 $(nx)×$(ny)×$(nz) ndof=$n fixed=$(length(fixed_dofs)) " *
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"rel_u=$(round(rel_u; sigdigits=3)) rel_r=$(round(rel_r; sigdigits=3))")
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end
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# ----------------------------------------------------------------------------
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# Type stability: apply_K! must infer `Vector{Float64}` (==typeof(y)) end-to-end
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# ----------------------------------------------------------------------------
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@testset "apply_K!: type stability" begin
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mesh = _build_hex8_box(2, 1, 1)
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cache, asm, kernel, m = _setup(mesh, Hexahedron{8})
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n = cache.ndofs
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x = ones(n)
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y = zeros(n)
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apply_K!(y, cache, asm, kernel, m, x) # warmup
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rt = Base.promote_op(apply_K!, typeof(y), typeof(cache), typeof(asm),
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typeof(kernel), typeof(m), typeof(x))
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@test rt === Vector{Float64}
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code = code_typed(apply_K!,
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(typeof(y), typeof(cache), typeof(asm),
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typeof(kernel), typeof(m), typeof(x));
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optimize = true)
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@test !isempty(code)
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info = code[1]
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@test isconcretetype(info.second)
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println(" apply_K! inferred return type: $(info.second)")
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end
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