bench: Ipopt + MadNLP allocation profile script#71
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jack-champagne wants to merge 3 commits intofeat/madnlp-integrationfrom
Open
bench: Ipopt + MadNLP allocation profile script#71jack-champagne wants to merge 3 commits intofeat/madnlp-integrationfrom
jack-champagne wants to merge 3 commits intofeat/madnlp-integrationfrom
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Adds benchmark/alloc_profile.jl which runs Profile.Allocs-traced solves on the shared bilinear toy problem for both in-tree NLP backends, saving AllocProfileResult JLD2s via HarmoniqsBenchmarks' benchmark_memory! / save_alloc_profile API. benchmark/Project.toml pins HarmoniqsBenchmarks to the feat/alloc-profile branch until that PR merges.
Codecov Report✅ All modified and coverable lines are covered by tests. 📢 Thoughts on this report? Let us know! |
analyze_allocs.jl ranks alloc hotspots by scaled bytes across all profile JLD2s in benchmark/results/allocs/ with noise-frame filtering. Companion to the existing alloc_profile.jl driver. alloc_profile.jl: coerce MadNLP.ERROR to Int for MadNLPOptions — symmetric to Piccolissimo commit 472fe4d.
Identified by Gennadi. abs2(tr(U_goal'·U))/n² is phase-insensitive, so +im·U_goal and -im·U_goal are equally valid optima. With free Δt, solvers fall into different basins depending on init + step sequence; with fixed Δt, both consistently land in the same basin.
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Summary
benchmark/alloc_profile.jl— standalone Julia script that runsDirectTrajOpt.solve!underProfile.Allocsfor both Ipopt and MadNLP on the shared bilinear toy problem, saving oneAllocProfileResultJLD2 per solver viaHarmoniqsBenchmarks.benchmark_memory!/save_alloc_profile.benchmark/Project.tomlwith DTO + the two NLP backends +HarmoniqsBenchmarks(pinned tofeat/alloc-profileuntil HarmoniqsBenchmarks.jl#1 merges)./benchmark/results/so local profile output stays out of history.The sibling
Piccolissimo.jlPR covers the Altissimo+MadNLP+Ipopt three-way on an X-gate; this PR is the DTO-only lane that tracks Ipopt/MadNLP performance over time on DTO's own test fixture.Rationale
sample_ratedefaults to0.01inmain()— Ipopt/MadNLP generate orders of magnitude more fine-grained allocations than asample_rate=1.0trace can complete in reasonable wall time (an N=10 bilinear toy hangs 15+ minutes at 1.0).0.01still gives statistically useful traces for hot-path triage.JIT warmup runs on a throwaway
deepcopyof the problem before the profiled pass so compile-time allocations stay out of the recorded trace.Dependencies
Blocked on HarmoniqsBenchmarks.jl#1 merging — once it does, drop the
rev =pin frombenchmark/Project.toml.Test plan
julia --project=benchmark benchmark/alloc_profile.jlproduces two*_allocs.jld2underbenchmark/results/allocs/AllocProfileResult.total_count > 0andtotal_bytes > 0for both solversload_alloc_profileroundtrips correctly