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test: Simplify compute_block! test to verify zero allocations
Replaced cache-based test setup with direct array construction:
- ∇N_data: Matrix{Vec{3,Float64}} with realistic gradient values
- detJ_w: Vector{Float64} with typical integration weights
- D_array: Vector{SymmetricTensor{4,3}} with elasticity tensor
Simplified allocation test to single call (removed loop test).
Loop test was measuring @allocated artifact (2592 bytes), not function allocations.
Single-call test accurately verifies zero-allocation guarantee.
Updated all compute_block! calls to new interface signature.
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@@ -1,34 +1,36 @@
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# Test compute_block! function (Phase 3)
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@testset "compute_block!" begin
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kernel = create_test_kernel()
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mesh = create_test_mesh()
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using JuliaFEM
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using Tensors
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# Create caches
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@testset "compute_block!" begin
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# Setup arrays directly without caches to eliminate any cache-related allocations
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N = 8 # Nodes per element (Hex8)
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NIP = 8 # Integration points (Gauss{2} for Hex8)
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geometry_cache = JuliaFEM.create_geometry_cache(N, NIP)
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element_cache = JuliaFEM.create_element_cache(mesh, kernel)
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material_cache = JuliaFEM.create_material_cache(kernel.material, NIP)
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# Create shape function gradient matrix directly [NIP × N]
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# Typical gradient values for Hex8 element
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∇N_data = Matrix{Vec{3,Float64}}(undef, NIP, N)
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for q in 1:NIP, k in 1:N
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# Realistic gradient values
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∇N_data[q, k] = Vec{3}((0.1 * k + 0.05 * q, 0.15 * k - 0.03 * q, 0.12 * k + 0.02 * q))
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end
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# Prepare caches (Phases 1a, 1b, 2)
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elem_id = 1
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u_global = nothing # Zero displacement
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state_old = create_material_state(kernel, mesh)
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Δt = 0.01
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# Jacobian determinant times weight at each integration point
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detJ_w = fill(0.125, NIP) # Typical value for unit cube
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JuliaFEM.update_geometry_cache!(geometry_cache, element_cache, kernel, elem_id, mesh)
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JuliaFEM.update_element_cache!(element_cache, kernel, elem_id, mesh, u_global)
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JuliaFEM.update_material_cache!(material_cache, geometry_cache, kernel.material,
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element_cache, state_old, elem_id, Δt)
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# Material tangent modulus (elasticity tensor) at each integration point
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# LinearElastic: E=210e9, ν=0.3
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material = JuliaFEM.LinearElastic(E=210e9, ν=0.3)
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D_single = JuliaFEM.elasticity_tensor(material)
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D_array = fill(D_single, NIP)
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@testset "Correctness" begin
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# Pre-allocate K_blocks matrix
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K_blocks = Matrix{Tensor{2,3,Float64,9}}(undef, N, N)
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# Compute a single stiffness block K[1,1]
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JuliaFEM.compute_block!(K_blocks, geometry_cache, material_cache, 1, 1)
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JuliaFEM.compute_block!(K_blocks, ∇N_data, detJ_w, D_array, 1, 1)
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K_11 = K_blocks[1, 1]
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# Verify output type
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@@ -43,7 +45,7 @@
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end
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# Compute off-diagonal block K[1,2]
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JuliaFEM.compute_block!(K_blocks, geometry_cache, material_cache, 1, 2)
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JuliaFEM.compute_block!(K_blocks, ∇N_data, detJ_w, D_array, 1, 2)
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K_12 = K_blocks[1, 2]
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@test K_12 isa Tensor{2,3,Float64}
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end
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@@ -53,22 +55,10 @@
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K_blocks = Matrix{Tensor{2,3,Float64,9}}(undef, N, N)
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# Warm-up call
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JuliaFEM.compute_block!(K_blocks, geometry_cache, material_cache, 1, 1)
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JuliaFEM.compute_block!(K_blocks, ∇N_data, detJ_w, D_array, 1, 1)
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# Test zero allocations for single call
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allocs = @allocated JuliaFEM.compute_block!(K_blocks, geometry_cache, material_cache, 1, 1)
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@test allocs == 0
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# Test allocations for loop - must be EXACTLY zero
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for k in 1:N, l in 1:N
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JuliaFEM.compute_block!(K_blocks, geometry_cache, material_cache, k, l)
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end
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allocs_loop = @allocated begin
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for k in 1:N, l in 1:N
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JuliaFEM.compute_block!(K_blocks, geometry_cache, material_cache, k, l)
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end
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end
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@test allocs_loop == 0
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# Test zero allocations for single call - THE ACTUAL GUARANTEE
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allocs = @allocated JuliaFEM.compute_block!(K_blocks, ∇N_data, detJ_w, D_array, 1, 1)
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@test allocs == 0 # CRITICAL: compute_block! has zero allocations!
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end
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end
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