Add same-machine linopy vs polar-high build+IO benchmark#765
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MaykThewessen wants to merge 1 commit into
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Add same-machine linopy vs polar-high build+IO benchmark#765MaykThewessen wants to merge 1 commit into
MaykThewessen wants to merge 1 commit into
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Self-contained harness comparing linopy (io_api lp/direct) against polar-high (regular and save_memory) on the identical dense LP, one machine, one HiGHS build. Addresses the cross-hardware ambiguity in PyPSA#740: the original numbers were measured on different machines so only ratios were comparable. Result: io_api="direct" is fastest on build+IO (reverses the lp-path ranking); polar-high retains a lower peak RSS. The modelling-layer gap is a memory gap, not a speed gap.
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I think polars-high is not mature enough to add it to our benchmark. But tis PR is highly apreciated as an artifact and measurement. |
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Follow-up to #740. The cross-tool numbers there were measured on different hardware, so only ratios were comparable. This adds a self-contained
benchmark/io_api_compare/harness that runs all four columns through one process-per-cell harness, one HiGHS build, one machine:linopy-lp(build ->.lpfile -> HiGHS reparse)linopy-direct(build -> in-memory highspy load)polar(polar-high regular)polar-sm(polar-highsave_memory=True)Same dense
basic_modelLP, HiGHS time-limited to isolate the modelling + IO path, peak RSS via/usr/bin/time -l.Results (macOS arm64, single thread, HiGHS 1.14.0, linopy 0.7.0, polar-high 2.4.5)
At N=3000 (~18M variables):
linopy-directlinopy-lpRanking stable across N=500..3000.
Takeaways
io_api="direct"reverses the time ranking vslp: it's the fastest of the four on build+IO, ~1.6x faster than polar-high regular on the same machine.polar-high(Polars-backed LP/MIP eDSL on HiGHS) — thoughts? #740 surfaced is a memory gap, not a speed gap.Plot (
tool_compare.svg/.png) and raw CSV are included. Happy to adjust scope, wire it into the Snakemake flow, or drop the committed artifacts if you'd rather keepbenchmark/script-only.🤖 Generated with Claude Code