Perf T2-7: Single vcat for ws construction#146
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Lock in expected ws vector structure and ws_z_indices for: - 3-player chain (1→2→3) with asymmetric dims - 2-player Nash game (no edges) These tests verify exact symbolic variable ordering and index ranges, ensuring any refactoring preserves correctness. Co-Authored-By: Claude Opus 4.6 <[email protected]>
Collect all symbolic vector pieces into a Vector{Vector{Num}} first,
then use reduce(vcat, pieces) for a single concatenation. This avoids
O(N²) intermediate allocations from repeated vcat in the inner loop.
Co-Authored-By: Claude Opus 4.6 <[email protected]>
Results show 1.5-32x speedup and ~74% allocation reduction: - N=3: 1.46x speedup - N=4: 2.05x speedup - N=5: 2.89x speedup, 73.8% fewer allocations - N=6: 31.94x speedup (quadratic vs linear scaling) Co-Authored-By: Claude Opus 4.6 <[email protected]>
Co-Authored-By: Claude Opus 4.6 <[email protected]>
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Summary
Replace repeated
vcatcalls in ws construction loop (O(N²) allocations) with a collect-then-reduce(vcat, pieces)pattern (O(N) allocations).Changes
src/problem_setup.jl: Collect all symbolic vector pieces intoVector{Vector{Num}}, then singlereduce(vcat, pieces)instead of repeatedws[i] = vcat(ws[i], ...)in inner loopstest/test_problem_setup.jl: Add exact symbolic content tests for ws vectors (chain 1→2→3 and Nash topologies)scripts/benchmark_ws_vcat.jl: Benchmark script comparing old vs new approachBenchmark Results
Allocation reduction (N=5): 52,768 → 13,840 bytes (73.8% reduction)
The superlinear speedup at N=6 demonstrates the quadratic-to-linear scaling improvement.
Testing
isequalfor all ws vectors between old and new approachChangelog
🤖 Generated with Claude Code