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Mar 5, 2025
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Type-stable compress and random order in benchmarks #198

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Type-stable compress and random order in benchmarks
gdalle Mar 5, 2025
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Ensure zero size
gdalle Mar 5, 2025
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gdalle Mar 5, 2025
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4 changes: 3 additions & 1 deletion benchmark/benchmarks.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,9 @@ for structure in [:nonsymmetric, :symmetric],
p in [2 / n, 5 / n, 10 / n]

problem = ColoringProblem(; structure, partition)
algo = GreedyColoringAlgorithm(; decompression, postprocessing=true)
algo = GreedyColoringAlgorithm(
RandomOrder(StableRNG(0), 0); decompression, postprocessing=true
)

# use several random matrices to reduce variance
nb_samples = 5
Expand Down
24 changes: 20 additions & 4 deletions src/decompression.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,11 @@ function compress end
function compress(A, result::AbstractColoringResult{structure,:column}) where {structure}
group = column_groups(result)
if isempty(group)
B = similar(A, size(A, 1), 0)
# ensure we get a Matrix and not a SparseMatrixCSC
B_model = stack([Int[]]; dims=2) do g
dropdims(sum(A[:, g]; dims=2); dims=2)
end
B = similar(B_model, size(A, 1), 0)
else
B = stack(group; dims=2) do g
dropdims(sum(A[:, g]; dims=2); dims=2)
Expand All @@ -59,7 +63,11 @@ end
function compress(A, result::AbstractColoringResult{structure,:row}) where {structure}
group = row_groups(result)
if isempty(group)
B = similar(A, 0, size(A, 2))
# ensure we get a Matrix and not a SparseMatrixCSC
B_model = stack([Int[]]; dims=1) do g
dropdims(sum(A[g, :]; dims=1); dims=1)
end
B = similar(B_model, 0, size(A, 2))
else
B = stack(group; dims=1) do g
dropdims(sum(A[g, :]; dims=1); dims=1)
Expand All @@ -74,14 +82,22 @@ function compress(
row_group = row_groups(result)
column_group = column_groups(result)
if isempty(row_group)
Br = similar(A, 0, size(A, 2))
# ensure we get a Matrix and not a SparseMatrixCSC
Br_model = stack([Int[]]; dims=1) do g
dropdims(sum(A[g, :]; dims=1); dims=1)
end
Br = similar(Br_model, 0, size(A, 2))
else
Br = stack(row_group; dims=1) do g
dropdims(sum(A[g, :]; dims=1); dims=1)
end
end
if isempty(column_group)
Bc = similar(A, size(A, 1), 0)
# ensure we get a Matrix and not a SparseMatrixCSC
Bc_model = stack([Int[]]; dims=2) do g
dropdims(sum(A[:, g]; dims=2); dims=2)
end
Bc = similar(Bc_model, size(A, 1), 0)
else
Bc = stack(column_group; dims=2) do g
dropdims(sum(A[:, g]; dims=2); dims=2)
Expand Down
43 changes: 29 additions & 14 deletions test/type_stability.jl
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Expand Up @@ -11,19 +11,17 @@ rng = StableRNG(63)

@testset "Sparse coloring" begin
n = 10
A = sprand(rng, n, n, 5 / n)
A = sparse(Symmetric(sprand(rng, n, n, 5 / n)))

# ADTypes
@testset "ADTypes" begin
@test_opt target_modules = (SparseMatrixColorings,) column_coloring(
A, GreedyColoringAlgorithm()
)
@test_opt target_modules = (SparseMatrixColorings,) row_coloring(
A, GreedyColoringAlgorithm()
)
@test_opt target_modules = (SparseMatrixColorings,) symmetric_coloring(
Symmetric(A), GreedyColoringAlgorithm()
)
@test_opt column_coloring(A, GreedyColoringAlgorithm())
@test_opt row_coloring(A, GreedyColoringAlgorithm())
@test_opt symmetric_coloring(Symmetric(A), GreedyColoringAlgorithm())

@inferred column_coloring(A, GreedyColoringAlgorithm())
@inferred row_coloring(A, GreedyColoringAlgorithm())
@inferred symmetric_coloring(Symmetric(A), GreedyColoringAlgorithm())
end

@testset "$structure - $partition - $decompression" for (
Expand All @@ -36,7 +34,12 @@ rng = StableRNG(63)
(:nonsymmetric, :bidirectional, :direct),
(:nonsymmetric, :bidirectional, :substitution),
]
@test_opt target_modules = (SparseMatrixColorings,) coloring(
@test_opt coloring(
A,
ColoringProblem(; structure, partition),
GreedyColoringAlgorithm(; decompression),
)
@inferred coloring(
A,
ColoringProblem(; structure, partition),
GreedyColoringAlgorithm(; decompression),
Expand All @@ -55,7 +58,12 @@ end;
(structure, partition, decompression) in
[(:nonsymmetric, :column, :direct), (:nonsymmetric, :row, :direct)]

@test_opt target_modules = (SparseMatrixColorings,) coloring(
@test_opt coloring(
A,
ColoringProblem(; structure, partition),
GreedyColoringAlgorithm(; decompression),
)
@inferred coloring(
A,
ColoringProblem(; structure, partition),
GreedyColoringAlgorithm(; decompression),
Expand Down Expand Up @@ -88,15 +96,21 @@ end;
Br, Bc = compress(A, result)
@testset "Full decompression" begin
@test_opt compress(A, result)
@test_opt decompress(Br, Bc, result) ≈ A0
@test_opt decompress(Br, Bc, result)
@test_opt decompress!(respectful_similar(A), Br, Bc, result)

@inferred compress(A, result)
@inferred decompress(Br, Bc, result)
end
else
B = compress(A, result)
@testset "Full decompression" begin
@test_opt compress(A, result)
@test_opt decompress(B, result) ≈ A0
@test_opt decompress(B, result)
@test_opt decompress!(respectful_similar(A), B, result)

@inferred compress(A, result)
@inferred decompress(B, result)
end
@testset "Single-color decompression" begin
if decompression == :direct
Expand Down Expand Up @@ -145,5 +159,6 @@ end;
)
B = compress(A, result)
@test_opt decompress(B, result)
@inferred decompress(B, result)
end
end;