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Use the same Tag for the sparse Hessian of the Lagrangian #351

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Use the same Tag for the sparse Hessian of the Lagrangian #351

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amontoison
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@amontoison amontoison requested a review from tmigot June 5, 2025 04:07
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github-actions bot commented Jun 5, 2025 •
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Package name latest stable
ExpressionTreeForge
JSOSuite
PartiallySeparableNLPModels
PartiallySeparableSolvers
SolverTest

@jbcaillau
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thanks @amontoison for the update. please tag us again when this is released so that we can test it 🤞🏽

amontoison
amontoison commented Jun 5, 2025
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src/sparse_hessian.jl
lz::Vector{ForwardDiff.Dual{Tag, T, 1}}
glz::Vector{ForwardDiff.Dual{Tag, T, 1}}
lz::Vector{ForwardDiff.Dual{Val{:SparseADHessian}, T, 1}}
glz::Vector{ForwardDiff.Dual{Val{:SparseADHessian}, T, 1}}
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I had no idea it could work this way. I thought the first type was connected to the function !?

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@amontoison amontoison Jun 7, 2025 •
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The Tag is just used to know what is the inner / outer function when we have nested differentiation.
The Tag can be the type of the function, Nothing or a custom symbol.
It will not impact performance, it is just for correctness.

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Benchmark result

Judge result

Benchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jl

Job Properties

  • Time of benchmarks:
    • Target: 7 Jun 2025 - 01:01
    • Baseline: 7 Jun 2025 - 01:18
  • Package commits:
  • Julia commits:
    • Target: 760b2e5
    • Baseline: 760b2e5
  • Julia command flags:
    • Target: None
    • Baseline: None
  • Environment variables:
    • Target: None
    • Baseline: None

Results

A ratio greater than 1.0 denotes a possible regression (marked with ❌), while a ratio less
than 1.0 denotes a possible improvement (marked with ✅). Brackets display tolerances for the benchmark estimates. Only significant results - results
that indicate possible regressions or improvements - are shown below (thus, an empty table means that all
benchmark results remained invariant between builds).

ID time ratio memory ratio
["jac_coord", "optimized", "Float32", "scalable", "sparse", "elec"] 1.10 (5%) ❌ 1.00 (1%)
["jac_coord", "optimized", "Float32", "scalable", "sparse", "hovercraft1d"] 1.32 (5%) ❌ 1.00 (1%)
["jac_coord", "optimized", "Float32", "scalable", "sparse", "polygon1"] 1.39 (5%) ❌ 1.00 (1%)
["jac_coord", "optimized", "Float32", "scalable", "sparse", "structural"] 1.19 (5%) ❌ 1.00 (1%)
["jac_coord", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 1.34 (5%) ❌ 1.00 (1%)
["jac_coord", "optimized", "Float64", "scalable", "sparse", "polygon1"] 1.26 (5%) ❌ 1.00 (1%)
["jac_coord", "optimized", "Float64", "scalable", "sparse", "structural"] 1.06 (5%) ❌ 1.00 (1%)
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "broyden3d"] 1.08 (5%) ❌ 1.00 (1%)
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "dixon3dq"] 1.14 (5%) ❌ 1.00 (1%)
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "errinros_mod"] 1.07 (5%) ❌ 1.00 (1%)
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "freuroth"] 1.08 (5%) ❌ 1.00 (1%)
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "hovercraft1d"] 1.18 (5%) ❌ 1.00 (1%)
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "penalty1"] 0.93 (5%) ✅ 1.00 (1%)
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "tquartic"] 1.16 (5%) ❌ 1.00 (1%)
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglinb"] 1.19 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 1.06 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "elec"] 1.06 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 1.15 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "marine"] 1.05 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "polygon1"] 1.16 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "structural"] 1.06 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "camshape"] 1.33 (5%) ❌ 1.01 (1%) ❌
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "catenary"] 1.51 (5%) ❌ 1.01 (1%) ❌
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "chain"] 1.30 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "channel"] 1.21 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "clnlbeam"] 1.54 (5%) ❌ 1.01 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "controlinvestment"] 1.41 (5%) ❌ 1.01 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "elec"] 1.19 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "marine"] 1.43 (5%) ❌ 1.01 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon3"] 1.33 (5%) ❌ 1.01 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "robotarm"] 1.30 (5%) ❌ 1.00 (1%)

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["jac_coord", "optimized", "Float32", "scalable", "sparse"]
  • ["jac_coord", "optimized", "Float64", "scalable", "sparse"]
  • ["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse"]
  • ["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse"]
  • ["jacobian_backend", "optimized", "Float64", "scalable", "sparse"]
  • ["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics"]

Julia versioninfo

Target

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz       9112 s          0 s        499 s      16434 s          0 s
       #2     0 MHz      12859 s          0 s        496 s      12721 s          0 s
       #3     0 MHz       9225 s          0 s        576 s      16234 s          0 s
       #4     0 MHz       8822 s          0 s        509 s      16723 s          0 s
  Memory: 15.620769500732422 GB (13383.8671875 MB free)
  Uptime: 2616.96 sec
  Load Avg:  1.12  1.09  1.29
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Baseline

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      12597 s          0 s        651 s      22939 s          0 s
       #2     0 MHz      16697 s          0 s        670 s      18856 s          0 s
       #3     0 MHz      12280 s          0 s        742 s      23160 s          0 s
       #4     0 MHz      12564 s          0 s        674 s      22964 s          0 s
  Memory: 15.620769500732422 GB (13234.16015625 MB free)
  Uptime: 3633.09 sec
  Load Avg:  1.15  1.15  1.32
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Target result

Benchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jl

Job Properties

  • Time of benchmark: 7 Jun 2025 - 01:01
  • Package commit: 6ab12a2
  • Julia commit: 760b2e5
  • Julia command flags: None
  • Environment variables: None

Results

Below is a table of this job's results, obtained by running the benchmarks.
The values listed in the ID column have the structure [parent_group, child_group, ..., key], and can be used to
index into the BaseBenchmarks suite to retrieve the corresponding benchmarks.
The percentages accompanying time and memory values in the below table are noise tolerances. The "true"
time/memory value for a given benchmark is expected to fall within this percentage of the reported value.
An empty cell means that the value was zero.

ID time GC time memory allocations
["jac_coord", "optimized", "Float32", "scalable", "sparse", "camshape"] 41.718 μs (5%) 20.20 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "catenary"] 20.679 μs (5%) 8.45 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "chain"] 32.922 μs (5%) 14.32 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "channel"] 1.743 ms (5%) 30.88 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "clnlbeam"] 41.308 μs (5%) 11.01 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "controlinvestment"] 88.045 μs (5%) 8.45 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "elec"] 12.984 μs (5%) 4.57 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "hovercraft1d"] 1.207 μs (5%) 7.90 KiB (1%) 4
["jac_coord", "optimized", "Float32", "scalable", "sparse", "marine"] 40.545 μs (5%) 8.95 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "polygon1"] 1.000 μs (5%) 4.02 KiB (1%) 4
["jac_coord", "optimized", "Float32", "scalable", "sparse", "polygon3"] 20.769 μs (5%) 12.38 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "robotarm"] 34.565 μs (5%) 13.70 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "structural"] 3.264 μs (5%) 50.52 KiB (1%) 4
["jac_coord", "optimized", "Float64", "scalable", "sparse", "camshape"] 49.352 μs (5%) 39.70 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "catenary"] 22.191 μs (5%) 16.20 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "chain"] 42.569 μs (5%) 27.95 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "channel"] 2.076 ms (5%) 61.13 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 44.994 μs (5%) 21.38 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "controlinvestment"] 89.708 μs (5%) 16.26 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "elec"] 12.824 μs (5%) 8.45 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 1.243 μs (5%) 15.71 KiB (1%) 4
["jac_coord", "optimized", "Float64", "scalable", "sparse", "marine"] 41.096 μs (5%) 17.20 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "polygon1"] 847.310 ns (5%) 7.90 KiB (1%) 4
["jac_coord", "optimized", "Float64", "scalable", "sparse", "polygon3"] 21.410 μs (5%) 24.07 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "robotarm"] 39.113 μs (5%) 26.70 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "structural"] 5.228 μs (5%) 100.90 KiB (1%) 4
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "arglina"] 33.381 ms (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "arglinb"] 5.271 ms (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "bdqrtic"] 38.181 μs (5%) 23.87 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "brownal"] 5.721 ms (5%) 3.82 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "broyden3d"] 20.538 μs (5%) 12.24 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "brybnd"] 121.477 μs (5%) 27.80 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "dixon3dq"] 14.387 μs (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "errinros_mod"] 34.905 μs (5%) 12.24 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "freuroth"] 21.270 μs (5%) 16.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "hovercraft1d"] 7.063 μs (5%) 1.78 KiB (1%) 5
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "integreq"] 34.584 s (5%) 3.82 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "morebv"] 224.199 μs (5%) 12.24 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "penalty1"] 2.887 ms (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "power"] 2.102 ms (5%) 4.43 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "sbrybnd"] 118.442 μs (5%) 27.80 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "spmsrtls"] 37.690 μs (5%) 19.99 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "tquartic"] 15.209 μs (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglina"] 36.618 ms (5%) 15.26 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglinb"] 7.731 ms (5%) 15.26 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "bdqrtic"] 38.572 μs (5%) 47.18 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brownal"] 6.222 ms (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "broyden3d"] 20.037 μs (5%) 23.93 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brybnd"] 129.262 μs (5%) 55.05 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "dixon3dq"] 12.904 μs (5%) 16.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "errinros_mod"] 45.776 μs (5%) 23.93 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "freuroth"] 20.659 μs (5%) 31.74 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "hovercraft1d"] 6.342 μs (5%) 3.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "integreq"] 38.343 s (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "morebv"] 184.906 μs (5%) 23.93 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "penalty1"] 3.071 ms (5%) 16.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "power"] 2.097 ms (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "sbrybnd"] 120.575 μs (5%) 55.05 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "spmsrtls"] 36.829 μs (5%) 39.49 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "tquartic"] 14.237 μs (5%) 16.12 KiB (1%) 6
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "camshape"] 587.409 μs (5%) 1.79 MiB (1%) 21396
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "catenary"] 311.883 μs (5%) 779.49 KiB (1%) 8708
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "chain"] 413.554 μs (5%) 1.23 MiB (1%) 10772
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "channel"] 2.564 ms (5%) 4.35 MiB (1%) 63530
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 228.959 μs (5%) 712.44 KiB (1%) 6733
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "controlinvestment"] 373.880 μs (5%) 1.12 MiB (1%) 12866
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "elec"] 210.603 μs (5%) 690.92 KiB (1%) 6333
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 120.085 μs (5%) 433.60 KiB (1%) 3389
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "marine"] 607.105 μs (5%) 1.07 MiB (1%) 13619
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "polygon1"] 111.839 μs (5%) 359.61 KiB (1%) 3332
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "polygon3"] 360.976 μs (5%) 1.11 MiB (1%) 11363
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "robotarm"] 452.718 μs (5%) 1.20 MiB (1%) 12706
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "structural"] 1.228 ms (5%) 6.74 MiB (1%) 18534
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "camshape"] 135.548 ms (5%) 44.10 MiB (1%) 771601
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "catenary"] 60.583 ms (5%) 16.92 MiB (1%) 289105
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "chain"] 91.314 ms (5%) 24.36 MiB (1%) 431425
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "channel"] 379.561 ms (5%) 133.40 MiB (1%) 2411014
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "clnlbeam"] 40.521 ms (5%) 10.65 MiB (1%) 183014
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "controlinvestment"] 57.398 ms (5%) 18.06 MiB (1%) 314983
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "elec"] 19.068 ms (5%) 7.62 MiB (1%) 133225
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "hovercraft1d"] 1.880 ms (5%) 1.34 MiB (1%) 22864
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "marine"] 35.600 ms (5%) 11.68 MiB (1%) 201125
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon1"] 1.915 ms (5%) 1.27 MiB (1%) 22847
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon3"] 51.318 ms (5%) 16.74 MiB (1%) 298848
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "robotarm"] 76.866 ms (5%) 23.93 MiB (1%) 415569
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "structural"] 7.872 ms (5%) 10.08 MiB (1%) 88849

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["jac_coord", "optimized", "Float32", "scalable", "sparse"]
  • ["jac_coord", "optimized", "Float64", "scalable", "sparse"]
  • ["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse"]
  • ["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse"]
  • ["jacobian_backend", "optimized", "Float64", "scalable", "sparse"]
  • ["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics"]

Julia versioninfo

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz       9112 s          0 s        499 s      16434 s          0 s
       #2     0 MHz      12859 s          0 s        496 s      12721 s          0 s
       #3     0 MHz       9225 s          0 s        576 s      16234 s          0 s
       #4     0 MHz       8822 s          0 s        509 s      16723 s          0 s
  Memory: 15.620769500732422 GB (13383.8671875 MB free)
  Uptime: 2616.96 sec
  Load Avg:  1.12  1.09  1.29
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Baseline result

Benchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jl

Job Properties

  • Time of benchmark: 7 Jun 2025 - 01:18
  • Package commit: fd0d248
  • Julia commit: 760b2e5
  • Julia command flags: None
  • Environment variables: None

Results

Below is a table of this job's results, obtained by running the benchmarks.
The values listed in the ID column have the structure [parent_group, child_group, ..., key], and can be used to
index into the BaseBenchmarks suite to retrieve the corresponding benchmarks.
The percentages accompanying time and memory values in the below table are noise tolerances. The "true"
time/memory value for a given benchmark is expected to fall within this percentage of the reported value.
An empty cell means that the value was zero.

ID time GC time memory allocations
["jac_coord", "optimized", "Float32", "scalable", "sparse", "camshape"] 40.646 μs (5%) 20.20 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "catenary"] 19.938 μs (5%) 8.45 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "chain"] 31.819 μs (5%) 14.32 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "channel"] 1.725 ms (5%) 30.88 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "clnlbeam"] 40.376 μs (5%) 11.01 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "controlinvestment"] 87.544 μs (5%) 8.45 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "elec"] 11.853 μs (5%) 4.57 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "hovercraft1d"] 911.700 ns (5%) 7.90 KiB (1%) 4
["jac_coord", "optimized", "Float32", "scalable", "sparse", "marine"] 38.853 μs (5%) 8.95 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "polygon1"] 721.889 ns (5%) 4.02 KiB (1%) 4
["jac_coord", "optimized", "Float32", "scalable", "sparse", "polygon3"] 20.399 μs (5%) 12.38 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "robotarm"] 33.433 μs (5%) 13.70 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "structural"] 2.738 μs (5%) 50.52 KiB (1%) 4
["jac_coord", "optimized", "Float64", "scalable", "sparse", "camshape"] 49.342 μs (5%) 39.70 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "catenary"] 22.292 μs (5%) 16.20 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "chain"] 42.650 μs (5%) 27.95 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "channel"] 2.038 ms (5%) 61.13 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 45.104 μs (5%) 21.38 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "controlinvestment"] 89.267 μs (5%) 16.26 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "elec"] 12.463 μs (5%) 8.45 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 930.700 ns (5%) 15.71 KiB (1%) 4
["jac_coord", "optimized", "Float64", "scalable", "sparse", "marine"] 40.706 μs (5%) 17.20 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "polygon1"] 669.821 ns (5%) 7.90 KiB (1%) 4
["jac_coord", "optimized", "Float64", "scalable", "sparse", "polygon3"] 21.410 μs (5%) 24.07 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "robotarm"] 39.053 μs (5%) 26.70 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "structural"] 4.951 μs (5%) 100.90 KiB (1%) 4
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "arglina"] 33.485 ms (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "arglinb"] 5.291 ms (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "bdqrtic"] 36.559 μs (5%) 23.87 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "brownal"] 5.626 ms (5%) 3.82 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "broyden3d"] 18.976 μs (5%) 12.24 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "brybnd"] 118.050 μs (5%) 27.80 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "dixon3dq"] 12.634 μs (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "errinros_mod"] 32.772 μs (5%) 12.24 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "freuroth"] 19.607 μs (5%) 16.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "hovercraft1d"] 5.969 μs (5%) 1.78 KiB (1%) 5
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "integreq"] 34.632 s (5%) 3.82 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "morebv"] 220.864 μs (5%) 12.24 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "penalty1"] 3.094 ms (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "power"] 2.094 ms (5%) 4.43 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "sbrybnd"] 117.079 μs (5%) 27.80 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "spmsrtls"] 36.448 μs (5%) 19.99 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "tquartic"] 13.094 μs (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglina"] 35.970 ms (5%) 15.26 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglinb"] 6.507 ms (5%) 15.26 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "bdqrtic"] 38.412 μs (5%) 47.18 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brownal"] 6.174 ms (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "broyden3d"] 20.027 μs (5%) 23.93 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brybnd"] 129.443 μs (5%) 55.05 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "dixon3dq"] 13.265 μs (5%) 16.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "errinros_mod"] 45.846 μs (5%) 23.93 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "freuroth"] 20.849 μs (5%) 31.74 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "hovercraft1d"] 6.434 μs (5%) 3.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "integreq"] 38.301 s (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "morebv"] 181.599 μs (5%) 23.93 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "penalty1"] 3.070 ms (5%) 16.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "power"] 2.097 ms (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "sbrybnd"] 120.305 μs (5%) 55.05 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "spmsrtls"] 37.119 μs (5%) 39.49 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "tquartic"] 14.036 μs (5%) 16.12 KiB (1%) 6
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "camshape"] 586.487 μs (5%) 1.79 MiB (1%) 21395
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "catenary"] 299.891 μs (5%) 779.29 KiB (1%) 8707
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "chain"] 404.858 μs (5%) 1.23 MiB (1%) 10771
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "channel"] 2.521 ms (5%) 4.35 MiB (1%) 63529
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 216.235 μs (5%) 712.23 KiB (1%) 6732
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "controlinvestment"] 358.901 μs (5%) 1.12 MiB (1%) 12865
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "elec"] 198.071 μs (5%) 690.72 KiB (1%) 6332
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 104.745 μs (5%) 433.40 KiB (1%) 3388
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "marine"] 575.847 μs (5%) 1.07 MiB (1%) 13618
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "polygon1"] 96.691 μs (5%) 359.41 KiB (1%) 3331
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "polygon3"] 351.238 μs (5%) 1.11 MiB (1%) 11362
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "robotarm"] 439.532 μs (5%) 1.20 MiB (1%) 12717
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "structural"] 1.159 ms (5%) 6.74 MiB (1%) 18533
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "camshape"] 102.057 ms (5%) 43.55 MiB (1%) 762600
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "catenary"] 40.039 ms (5%) 16.74 MiB (1%) 286116
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "chain"] 70.226 ms (5%) 24.27 MiB (1%) 429930
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "channel"] 312.617 ms (5%) 133.21 MiB (1%) 2408013
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "clnlbeam"] 26.361 ms (5%) 10.59 MiB (1%) 182017
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "controlinvestment"] 40.595 ms (5%) 17.96 MiB (1%) 313485
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "elec"] 15.982 ms (5%) 7.62 MiB (1%) 133224
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "hovercraft1d"] 1.927 ms (5%) 1.34 MiB (1%) 22863
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "marine"] 24.812 ms (5%) 11.60 MiB (1%) 199753
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon1"] 1.936 ms (5%) 1.27 MiB (1%) 22846
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon3"] 38.626 ms (5%) 16.64 MiB (1%) 297347
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "robotarm"] 59.262 ms (5%) 23.93 MiB (1%) 415580
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "structural"] 7.917 ms (5%) 10.08 MiB (1%) 88848

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["jac_coord", "optimized", "Float32", "scalable", "sparse"]
  • ["jac_coord", "optimized", "Float64", "scalable", "sparse"]
  • ["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse"]
  • ["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse"]
  • ["jacobian_backend", "optimized", "Float64", "scalable", "sparse"]
  • ["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics"]

Julia versioninfo

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      12597 s          0 s        651 s      22939 s          0 s
       #2     0 MHz      16697 s          0 s        670 s      18856 s          0 s
       #3     0 MHz      12280 s          0 s        742 s      23160 s          0 s
       #4     0 MHz      12564 s          0 s        674 s      22964 s          0 s
  Memory: 15.620769500732422 GB (13234.16015625 MB free)
  Uptime: 3633.09 sec
  Load Avg:  1.15  1.15  1.32
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Runtime information

Runtime Info
BLAS #threads 2
BLAS.vendor() lbt
Sys.CPU_THREADS 4

lscpu output:

Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        48 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               4
On-line CPU(s) list:                  0-3
Vendor ID:                            AuthenticAMD
Model name:                           AMD EPYC 7763 64-Core Processor
CPU family:                           25
Model:                                1
Thread(s) per core:                   2
Core(s) per socket:                   2
Socket(s):                            1
Stepping:                             1
BogoMIPS:                             4890.85
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves user_shstk clzero xsaveerptr rdpru arat npt nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload umip vaes vpclmulqdq rdpid fsrm
Virtualization:                       AMD-V
Hypervisor vendor:                    Microsoft
Virtualization type:                  full
L1d cache:                            64 KiB (2 instances)
L1i cache:                            64 KiB (2 instances)
L2 cache:                             1 MiB (2 instances)
L3 cache:                             32 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-3
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Vulnerable: Safe RET, no microcode
Vulnerability Spec store bypass:      Vulnerable
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Retpolines; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected
Cpu Property Value
Brand AMD EPYC 7763 64-Core Processor
Vendor :AMD
Architecture :Unknown
Model Family: 0xaf, Model: 0x01, Stepping: 0x01, Type: 0x00
Cores 16 physical cores, 16 logical cores (on executing CPU)
No Hyperthreading hardware capability detected
Clock Frequencies Not supported by CPU
Data Cache Level 1:3 : (32, 512, 32768) kbytes
64 byte cache line size
Address Size 48 bits virtual, 48 bits physical
SIMD 256 bit = 32 byte max. SIMD vector size
Time Stamp Counter TSC is accessible via rdtsc
TSC runs at constant rate (invariant from clock frequency)
Perf. Monitoring Performance Monitoring Counters (PMC) are not supported
Hypervisor Yes, Microsoft

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Benchmark result

Judge result

Benchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jl

Job Properties

  • Time of benchmarks:
    • Target: 7 Jun 2025 - 01:01
    • Baseline: 7 Jun 2025 - 01:19
  • Package commits:
  • Julia commits:
    • Target: 760b2e5
    • Baseline: 760b2e5
  • Julia command flags:
    • Target: None
    • Baseline: None
  • Environment variables:
    • Target: None
    • Baseline: None

Results

A ratio greater than 1.0 denotes a possible regression (marked with ❌), while a ratio less
than 1.0 denotes a possible improvement (marked with ✅). Brackets display tolerances for the benchmark estimates. Only significant results - results
that indicate possible regressions or improvements - are shown below (thus, an empty table means that all
benchmark results remained invariant between builds).

ID time ratio memory ratio
["jac_coord", "optimized", "Float32", "scalable", "sparse", "channel"] 0.93 (5%) ✅ 1.00 (1%)
["jac_coord", "optimized", "Float32", "scalable", "sparse", "elec"] 0.92 (5%) ✅ 1.00 (1%)
["jac_coord", "optimized", "Float32", "scalable", "sparse", "hovercraft1d"] 0.71 (5%) ✅ 1.00 (1%)
["jac_coord", "optimized", "Float32", "scalable", "sparse", "polygon1"] 0.65 (5%) ✅ 1.00 (1%)
["jac_coord", "optimized", "Float32", "scalable", "sparse", "polygon3"] 0.95 (5%) ✅ 1.00 (1%)
["jac_coord", "optimized", "Float32", "scalable", "sparse", "structural"] 0.90 (5%) ✅ 1.00 (1%)
["jac_coord", "optimized", "Float64", "scalable", "sparse", "camshape"] 1.56 (5%) ❌ 1.00 (1%)
["jac_coord", "optimized", "Float64", "scalable", "sparse", "polygon1"] 1.10 (5%) ❌ 1.00 (1%)
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "broyden3d"] 0.95 (5%) ✅ 1.00 (1%)
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "dixon3dq"] 0.95 (5%) ✅ 1.00 (1%)
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "errinros_mod"] 1.49 (5%) ❌ 1.00 (1%)
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "errinros_mod"] 1.11 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "polygon1"] 1.10 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "catenary"] 1.08 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "chain"] 1.09 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "clnlbeam"] 1.09 (5%) ❌ 1.01 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "controlinvestment"] 1.08 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "elec"] 1.09 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "hovercraft1d"] 1.05 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "marine"] 0.93 (5%) ✅ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon1"] 1.06 (5%) ❌ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon3"] 0.95 (5%) ✅ 1.00 (1%)
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "structural"] 1.10 (5%) ❌ 1.00 (1%)

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["jac_coord", "optimized", "Float32", "scalable", "sparse"]
  • ["jac_coord", "optimized", "Float64", "scalable", "sparse"]
  • ["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse"]
  • ["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse"]
  • ["jacobian_backend", "optimized", "Float64", "scalable", "sparse"]
  • ["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics"]

Julia versioninfo

Target

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz       9063 s          2 s        572 s      16293 s          0 s
       #2     0 MHz      10061 s          0 s        558 s      15328 s          0 s
       #3     0 MHz       9396 s          0 s        530 s      16001 s          0 s
       #4     0 MHz      12231 s          0 s        496 s      13226 s          0 s
  Memory: 15.620769500732422 GB (13580.74609375 MB free)
  Uptime: 2605.67 sec
  Load Avg:  1.12  1.08  1.27
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Baseline

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      12253 s          2 s        732 s      23348 s          0 s
       #2     0 MHz      14155 s          0 s        727 s      21471 s          0 s
       #3     0 MHz      12640 s          0 s        716 s      22980 s          0 s
       #4     0 MHz      16084 s          0 s        674 s      19606 s          0 s
  Memory: 15.620769500732422 GB (13474.8359375 MB free)
  Uptime: 3647.94 sec
  Load Avg:  1.05  1.11  1.29
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Target result

Benchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jl

Job Properties

  • Time of benchmark: 7 Jun 2025 - 01:01
  • Package commit: 6ab12a2
  • Julia commit: 760b2e5
  • Julia command flags: None
  • Environment variables: None

Results

Below is a table of this job's results, obtained by running the benchmarks.
The values listed in the ID column have the structure [parent_group, child_group, ..., key], and can be used to
index into the BaseBenchmarks suite to retrieve the corresponding benchmarks.
The percentages accompanying time and memory values in the below table are noise tolerances. The "true"
time/memory value for a given benchmark is expected to fall within this percentage of the reported value.
An empty cell means that the value was zero.

ID time GC time memory allocations
["jac_coord", "optimized", "Float32", "scalable", "sparse", "camshape"] 41.587 μs (5%) 20.20 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "catenary"] 20.278 μs (5%) 8.45 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "chain"] 31.989 μs (5%) 14.32 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "channel"] 1.735 ms (5%) 30.88 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "clnlbeam"] 40.605 μs (5%) 11.01 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "controlinvestment"] 87.233 μs (5%) 8.45 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "elec"] 12.203 μs (5%) 4.57 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "hovercraft1d"] 883.151 ns (5%) 7.90 KiB (1%) 4
["jac_coord", "optimized", "Float32", "scalable", "sparse", "marine"] 38.862 μs (5%) 8.95 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "polygon1"] 618.275 ns (5%) 4.02 KiB (1%) 4
["jac_coord", "optimized", "Float32", "scalable", "sparse", "polygon3"] 20.227 μs (5%) 12.38 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "robotarm"] 33.994 μs (5%) 13.70 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "structural"] 3.252 μs (5%) 50.52 KiB (1%) 4
["jac_coord", "optimized", "Float64", "scalable", "sparse", "camshape"] 77.574 μs (5%) 39.70 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "catenary"] 22.642 μs (5%) 16.20 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "chain"] 43.080 μs (5%) 27.95 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "channel"] 2.044 ms (5%) 61.13 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 46.466 μs (5%) 21.38 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "controlinvestment"] 89.727 μs (5%) 16.26 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "elec"] 13.175 μs (5%) 8.45 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 1.405 μs (5%) 15.71 KiB (1%) 4
["jac_coord", "optimized", "Float64", "scalable", "sparse", "marine"] 41.768 μs (5%) 17.20 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "polygon1"] 1.053 μs (5%) 7.90 KiB (1%) 4
["jac_coord", "optimized", "Float64", "scalable", "sparse", "polygon3"] 21.971 μs (5%) 24.07 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "robotarm"] 41.287 μs (5%) 26.70 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "structural"] 5.771 μs (5%) 100.90 KiB (1%) 4
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "arglina"] 34.711 ms (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "arglinb"] 5.720 ms (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "bdqrtic"] 35.586 μs (5%) 23.87 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "brownal"] 5.809 ms (5%) 3.82 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "broyden3d"] 17.953 μs (5%) 12.24 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "brybnd"] 117.639 μs (5%) 27.80 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "dixon3dq"] 11.812 μs (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "errinros_mod"] 48.851 μs (5%) 12.24 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "freuroth"] 18.695 μs (5%) 16.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "hovercraft1d"] 5.832 μs (5%) 1.78 KiB (1%) 5
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "integreq"] 34.628 s (5%) 3.82 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "morebv"] 220.651 μs (5%) 12.24 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "penalty1"] 2.884 ms (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "power"] 2.020 ms (5%) 4.43 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "sbrybnd"] 117.699 μs (5%) 27.80 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "spmsrtls"] 35.406 μs (5%) 19.99 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "tquartic"] 12.733 μs (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglina"] 36.769 ms (5%) 15.26 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglinb"] 6.411 ms (5%) 15.26 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "bdqrtic"] 37.210 μs (5%) 47.18 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brownal"] 6.259 ms (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "broyden3d"] 19.888 μs (5%) 23.93 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brybnd"] 130.243 μs (5%) 55.05 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "dixon3dq"] 13.125 μs (5%) 16.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "errinros_mod"] 49.552 μs (5%) 23.93 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "freuroth"] 20.719 μs (5%) 31.74 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "hovercraft1d"] 6.302 μs (5%) 3.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "integreq"] 38.392 s (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "morebv"] 182.140 μs (5%) 23.93 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "penalty1"] 3.069 ms (5%) 16.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "power"] 2.096 ms (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "sbrybnd"] 120.144 μs (5%) 55.05 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "spmsrtls"] 37.670 μs (5%) 39.49 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "tquartic"] 13.736 μs (5%) 16.12 KiB (1%) 6
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "camshape"] 600.658 μs (5%) 1.79 MiB (1%) 21396
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "catenary"] 309.506 μs (5%) 779.49 KiB (1%) 8708
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "chain"] 423.659 μs (5%) 1.23 MiB (1%) 10772
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "channel"] 2.584 ms (5%) 4.35 MiB (1%) 63530
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 234.186 μs (5%) 712.44 KiB (1%) 6733
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "controlinvestment"] 374.336 μs (5%) 1.12 MiB (1%) 12866
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "elec"] 212.916 μs (5%) 690.92 KiB (1%) 6333
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 117.599 μs (5%) 433.60 KiB (1%) 3389
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "marine"] 599.666 μs (5%) 1.07 MiB (1%) 13619
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "polygon1"] 113.581 μs (5%) 359.61 KiB (1%) 3332
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "polygon3"] 366.322 μs (5%) 1.11 MiB (1%) 11363
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "robotarm"] 461.609 μs (5%) 1.20 MiB (1%) 12708
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "structural"] 1.280 ms (5%) 6.74 MiB (1%) 18534
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "camshape"] 113.154 ms (5%) 44.10 MiB (1%) 771601
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "catenary"] 48.161 ms (5%) 16.92 MiB (1%) 289105
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "chain"] 82.714 ms (5%) 24.36 MiB (1%) 431425
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "channel"] 332.964 ms (5%) 133.40 MiB (1%) 2411014
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "clnlbeam"] 30.600 ms (5%) 10.65 MiB (1%) 183014
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "controlinvestment"] 48.948 ms (5%) 18.06 MiB (1%) 314983
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "elec"] 19.505 ms (5%) 7.62 MiB (1%) 133225
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "hovercraft1d"] 2.162 ms (5%) 1.34 MiB (1%) 22864
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "marine"] 29.140 ms (5%) 11.68 MiB (1%) 201125
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon1"] 2.152 ms (5%) 1.27 MiB (1%) 22847
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon3"] 45.401 ms (5%) 16.74 MiB (1%) 298848
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "robotarm"] 69.006 ms (5%) 23.93 MiB (1%) 415571
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "structural"] 9.595 ms (5%) 10.08 MiB (1%) 88849

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["jac_coord", "optimized", "Float32", "scalable", "sparse"]
  • ["jac_coord", "optimized", "Float64", "scalable", "sparse"]
  • ["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse"]
  • ["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse"]
  • ["jacobian_backend", "optimized", "Float64", "scalable", "sparse"]
  • ["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics"]

Julia versioninfo

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz       9063 s          2 s        572 s      16293 s          0 s
       #2     0 MHz      10061 s          0 s        558 s      15328 s          0 s
       #3     0 MHz       9396 s          0 s        530 s      16001 s          0 s
       #4     0 MHz      12231 s          0 s        496 s      13226 s          0 s
  Memory: 15.620769500732422 GB (13580.74609375 MB free)
  Uptime: 2605.67 sec
  Load Avg:  1.12  1.08  1.27
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Baseline result

Benchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jl

Job Properties

  • Time of benchmark: 7 Jun 2025 - 01:19
  • Package commit: fd0d248
  • Julia commit: 760b2e5
  • Julia command flags: None
  • Environment variables: None

Results

Below is a table of this job's results, obtained by running the benchmarks.
The values listed in the ID column have the structure [parent_group, child_group, ..., key], and can be used to
index into the BaseBenchmarks suite to retrieve the corresponding benchmarks.
The percentages accompanying time and memory values in the below table are noise tolerances. The "true"
time/memory value for a given benchmark is expected to fall within this percentage of the reported value.
An empty cell means that the value was zero.

ID time GC time memory allocations
["jac_coord", "optimized", "Float32", "scalable", "sparse", "camshape"] 42.829 μs (5%) 20.20 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "catenary"] 21.089 μs (5%) 8.45 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "chain"] 33.262 μs (5%) 14.32 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "channel"] 1.867 ms (5%) 30.88 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "clnlbeam"] 42.008 μs (5%) 11.01 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "controlinvestment"] 87.162 μs (5%) 8.45 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "elec"] 13.224 μs (5%) 4.57 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "hovercraft1d"] 1.246 μs (5%) 7.90 KiB (1%) 4
["jac_coord", "optimized", "Float32", "scalable", "sparse", "marine"] 39.874 μs (5%) 8.95 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "polygon1"] 950.934 ns (5%) 4.02 KiB (1%) 4
["jac_coord", "optimized", "Float32", "scalable", "sparse", "polygon3"] 21.300 μs (5%) 12.38 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "robotarm"] 35.456 μs (5%) 13.70 KiB (1%) 9
["jac_coord", "optimized", "Float32", "scalable", "sparse", "structural"] 3.626 μs (5%) 50.52 KiB (1%) 4
["jac_coord", "optimized", "Float64", "scalable", "sparse", "camshape"] 49.813 μs (5%) 39.70 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "catenary"] 22.011 μs (5%) 16.20 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "chain"] 42.960 μs (5%) 27.95 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "channel"] 2.033 ms (5%) 61.13 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 46.937 μs (5%) 21.38 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "controlinvestment"] 89.186 μs (5%) 16.26 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "elec"] 12.834 μs (5%) 8.45 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 1.357 μs (5%) 15.71 KiB (1%) 4
["jac_coord", "optimized", "Float64", "scalable", "sparse", "marine"] 41.217 μs (5%) 17.20 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "polygon1"] 956.800 ns (5%) 7.90 KiB (1%) 4
["jac_coord", "optimized", "Float64", "scalable", "sparse", "polygon3"] 21.901 μs (5%) 24.07 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "robotarm"] 39.714 μs (5%) 26.70 KiB (1%) 9
["jac_coord", "optimized", "Float64", "scalable", "sparse", "structural"] 5.713 μs (5%) 100.90 KiB (1%) 4
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "arglina"] 34.034 ms (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "arglinb"] 5.606 ms (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "bdqrtic"] 37.008 μs (5%) 23.87 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "brownal"] 5.672 ms (5%) 3.82 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "broyden3d"] 18.915 μs (5%) 12.24 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "brybnd"] 119.783 μs (5%) 27.80 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "dixon3dq"] 12.453 μs (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "errinros_mod"] 32.842 μs (5%) 12.24 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "freuroth"] 19.477 μs (5%) 16.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "hovercraft1d"] 6.019 μs (5%) 1.78 KiB (1%) 5
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "integreq"] 34.772 s (5%) 3.82 MiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "morebv"] 221.332 μs (5%) 12.24 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "penalty1"] 2.885 ms (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "power"] 2.063 ms (5%) 4.43 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "sbrybnd"] 118.961 μs (5%) 27.80 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "spmsrtls"] 35.737 μs (5%) 19.99 KiB (1%) 6
["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse", "tquartic"] 13.214 μs (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglina"] 35.572 ms (5%) 15.26 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglinb"] 6.608 ms (5%) 15.26 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "bdqrtic"] 37.360 μs (5%) 47.18 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brownal"] 6.098 ms (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "broyden3d"] 19.807 μs (5%) 23.93 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brybnd"] 129.291 μs (5%) 55.05 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "dixon3dq"] 12.684 μs (5%) 16.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "errinros_mod"] 44.743 μs (5%) 23.93 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "freuroth"] 20.548 μs (5%) 31.74 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "hovercraft1d"] 6.109 μs (5%) 3.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "integreq"] 38.359 s (5%) 7.63 MiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "morebv"] 183.571 μs (5%) 23.93 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "penalty1"] 3.219 ms (5%) 16.12 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "power"] 2.174 ms (5%) 8.30 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "sbrybnd"] 119.993 μs (5%) 55.05 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "spmsrtls"] 37.129 μs (5%) 39.49 KiB (1%) 6
["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "tquartic"] 13.595 μs (5%) 16.12 KiB (1%) 6
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "camshape"] 592.784 μs (5%) 1.79 MiB (1%) 21395
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "catenary"] 319.825 μs (5%) 779.29 KiB (1%) 8707
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "chain"] 417.407 μs (5%) 1.23 MiB (1%) 10771
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "channel"] 2.541 ms (5%) 4.35 MiB (1%) 63534
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 225.931 μs (5%) 712.23 KiB (1%) 6732
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "controlinvestment"] 370.750 μs (5%) 1.12 MiB (1%) 12865
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "elec"] 207.085 μs (5%) 690.72 KiB (1%) 6332
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 112.149 μs (5%) 433.62 KiB (1%) 3398
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "marine"] 614.443 μs (5%) 1.07 MiB (1%) 13618
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "polygon1"] 102.801 μs (5%) 359.41 KiB (1%) 3331
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "polygon3"] 362.675 μs (5%) 1.11 MiB (1%) 11362
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "robotarm"] 446.150 μs (5%) 1.20 MiB (1%) 12717
["jacobian_backend", "optimized", "Float64", "scalable", "sparse", "structural"] 1.274 ms (5%) 6.74 MiB (1%) 18533
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "camshape"] 110.170 ms (5%) 44.10 MiB (1%) 771600
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "catenary"] 44.553 ms (5%) 16.92 MiB (1%) 289104
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "chain"] 75.546 ms (5%) 24.27 MiB (1%) 429930
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "channel"] 333.281 ms (5%) 133.40 MiB (1%) 2411018
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "clnlbeam"] 27.957 ms (5%) 10.59 MiB (1%) 182017
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "controlinvestment"] 45.446 ms (5%) 18.06 MiB (1%) 314982
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "elec"] 17.842 ms (5%) 7.62 MiB (1%) 133224
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "hovercraft1d"] 2.057 ms (5%) 1.34 MiB (1%) 22873
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "marine"] 31.423 ms (5%) 11.68 MiB (1%) 201124
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon1"] 2.031 ms (5%) 1.27 MiB (1%) 22846
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon3"] 48.029 ms (5%) 16.74 MiB (1%) 298847
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "robotarm"] 71.827 ms (5%) 23.93 MiB (1%) 415580
["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "structural"] 8.710 ms (5%) 10.08 MiB (1%) 88848

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["jac_coord", "optimized", "Float32", "scalable", "sparse"]
  • ["jac_coord", "optimized", "Float64", "scalable", "sparse"]
  • ["jac_coord_residual", "optimized", "Float32", "scalable_nls", "sparse"]
  • ["jac_coord_residual", "optimized", "Float64", "scalable_nls", "sparse"]
  • ["jacobian_backend", "optimized", "Float64", "scalable", "sparse"]
  • ["jacobian_backend", "optimized", "Float64", "scalable", "sparse_symbolics"]

Julia versioninfo

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      12253 s          2 s        732 s      23348 s          0 s
       #2     0 MHz      14155 s          0 s        727 s      21471 s          0 s
       #3     0 MHz      12640 s          0 s        716 s      22980 s          0 s
       #4     0 MHz      16084 s          0 s        674 s      19606 s          0 s
  Memory: 15.620769500732422 GB (13474.8359375 MB free)
  Uptime: 3647.94 sec
  Load Avg:  1.05  1.11  1.29
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Runtime information

Runtime Info
BLAS #threads 2
BLAS.vendor() lbt
Sys.CPU_THREADS 4

lscpu output:

Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        48 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               4
On-line CPU(s) list:                  0-3
Vendor ID:                            AuthenticAMD
Model name:                           AMD EPYC 7763 64-Core Processor
CPU family:                           25
Model:                                1
Thread(s) per core:                   2
Core(s) per socket:                   2
Socket(s):                            1
Stepping:                             1
BogoMIPS:                             4890.84
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves user_shstk clzero xsaveerptr rdpru arat npt nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload umip vaes vpclmulqdq rdpid fsrm
Virtualization:                       AMD-V
Hypervisor vendor:                    Microsoft
Virtualization type:                  full
L1d cache:                            64 KiB (2 instances)
L1i cache:                            64 KiB (2 instances)
L2 cache:                             1 MiB (2 instances)
L3 cache:                             32 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-3
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Vulnerable: Safe RET, no microcode
Vulnerability Spec store bypass:      Vulnerable
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Retpolines; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected
Cpu Property Value
Brand AMD EPYC 7763 64-Core Processor
Vendor :AMD
Architecture :Unknown
Model Family: 0xaf, Model: 0x01, Stepping: 0x01, Type: 0x00
Cores 16 physical cores, 16 logical cores (on executing CPU)
No Hyperthreading hardware capability detected
Clock Frequencies Not supported by CPU
Data Cache Level 1:3 : (32, 512, 32768) kbytes
64 byte cache line size
Address Size 48 bits virtual, 48 bits physical
SIMD 256 bit = 32 byte max. SIMD vector size
Time Stamp Counter TSC is accessible via rdtsc
TSC runs at constant rate (invariant from clock frequency)
Perf. Monitoring Performance Monitoring Counters (PMC) are not supported
Hypervisor Yes, Microsoft

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Benchmark result

Judge result

Benchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jl

Job Properties

  • Time of benchmarks:
    • Target: 7 Jun 2025 - 02:29
    • Baseline: 7 Jun 2025 - 03:28
  • Package commits:
  • Julia commits:
    • Target: 760b2e5
    • Baseline: 760b2e5
  • Julia command flags:
    • Target: None
    • Baseline: None
  • Environment variables:
    • Target: None
    • Baseline: None

Results

A ratio greater than 1.0 denotes a possible regression (marked with ❌), while a ratio less
than 1.0 denotes a possible improvement (marked with ✅). Brackets display tolerances for the benchmark estimates. Only significant results - results
that indicate possible regressions or improvements - are shown below (thus, an empty table means that all
benchmark results remained invariant between builds).

ID time ratio memory ratio
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "hovercraft1d"] 1.05 (5%) ❌ 1.00 (1%)
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglinb"] 1.17 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "camshape"] 1.40 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "catenary"] 1.86 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "chain"] 2.06 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "channel"] 2.26 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "clnlbeam"] 1.87 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "controlinvestment"] 1.92 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "elec"] 1.09 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "hovercraft1d"] 1.60 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "marine"] 1.92 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon1"] 2.05 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon3"] 1.67 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "robotarm"] 1.85 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "structural"] 1.43 (5%) ❌ 1.00 (1%)

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["hess_coord", "optimized", "Float64", "scalable_cons", "sparse"]
  • ["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse"]
  • ["hessian_backend", "optimized", "Float64", "scalable", "sparse"]
  • ["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics"]

Julia versioninfo

Target

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      18625 s          0 s        913 s      58599 s          0 s
       #2     0 MHz      30170 s          0 s        884 s      47067 s          0 s
       #3     0 MHz      17032 s          0 s       1020 s      60082 s          0 s
       #4     0 MHz      27003 s          0 s        956 s      50182 s          0 s
  Memory: 15.620769500732422 GB (12145.01171875 MB free)
  Uptime: 7828.58 sec
  Load Avg:  1.09  1.05  1.01
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Baseline

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      26469 s          0 s       1248 s      85858 s          0 s
       #2     0 MHz      45381 s          0 s       1212 s      66982 s          0 s
       #3     0 MHz      24593 s          0 s       1408 s      87578 s          0 s
       #4     0 MHz      35849 s          0 s       1344 s      76396 s          0 s
  Memory: 15.620769500732422 GB (12422.8828125 MB free)
  Uptime: 11376.3 sec
  Load Avg:  1.0  1.02  1.0
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Target result

Benchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jl

Job Properties

  • Time of benchmark: 7 Jun 2025 - 02:29
  • Package commit: 6ab12a2
  • Julia commit: 760b2e5
  • Julia command flags: None
  • Environment variables: None

Results

Below is a table of this job's results, obtained by running the benchmarks.
The values listed in the ID column have the structure [parent_group, child_group, ..., key], and can be used to
index into the BaseBenchmarks suite to retrieve the corresponding benchmarks.
The percentages accompanying time and memory values in the below table are noise tolerances. The "true"
time/memory value for a given benchmark is expected to fall within this percentage of the reported value.
An empty cell means that the value was zero.

ID time GC time memory allocations
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "camshape"] 407.732 ms (5%) 1.61 MiB (1%) 12348
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "catenary"] 13.200 ms (5%) 356.98 KiB (1%) 2390
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "chain"] 23.395 ms (5%) 275.29 KiB (1%) 1932
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "channel"] 829.273 ms (5%) 974.16 KiB (1%) 6742
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "clnlbeam"] 13.750 ms (5%) 120.85 KiB (1%) 802
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "controlinvestment"] 36.529 ms (5%) 275.29 KiB (1%) 1932
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "elec"] 909.787 s (5%) 383.299 ms 113.93 MiB (1%) 793214
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "hovercraft1d"] 567.901 μs (5%) 5.57 MiB (1%) 472
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "marine"] 362.093 ms (5%) 4.18 MiB (1%) 30600
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "polygon1"] 18.861 ms (5%) 206.63 KiB (1%) 1280
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "polygon3"] 74.135 ms (5%) 614.23 KiB (1%) 4406
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "robotarm"] 80.086 ms (5%) 810.79 KiB (1%) 5896
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "structural"] 13.757 ms (5%) 92.39 KiB (1%) 854
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglina"] 48.454 ms (5%) 328.33 KiB (1%) 2465
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglinb"] 54.193 ms (5%) 328.33 KiB (1%) 2465
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "bdqrtic"] 74.957 ms (5%) 335.41 KiB (1%) 2461
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brownal"] 18.380 s (5%) 27.029 ms 197.78 MiB (1%) 1466005
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "broyden3d"] 24.078 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brybnd"] 67.004 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "dixon3dq"] 8.972 ms (5%) 201.23 KiB (1%) 1469
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "errinros_mod"] 64.494 ms (5%) 336.18 KiB (1%) 2467
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "freuroth"] 73.884 ms (5%) 336.18 KiB (1%) 2467
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "hovercraft1d"] 1.697 ms (5%) 115.48 KiB (1%) 797
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "integreq"] 18.319 s (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "morebv"] 34.678 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "penalty1"] 19.202 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "power"] 2.813 ms (5%) 81.23 KiB (1%) 469
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "sbrybnd"] 96.420 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "spmsrtls"] 364.485 ms (5%) 1.82 MiB (1%) 13965
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "tquartic"] 12.179 ms (5%) 208.32 KiB (1%) 1465
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "camshape"] 19.325 ms (5%) 54.68 MiB (1%) 92726
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "catenary"] 6.962 ms (5%) 18.06 MiB (1%) 31373
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "chain"] 6.593 ms (5%) 13.33 MiB (1%) 40180
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "channel"] 20.925 ms (5%) 49.63 MiB (1%) 128024
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 6.533 ms (5%) 13.93 MiB (1%) 43419
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "controlinvestment"] 18.255 ms (5%) 45.43 MiB (1%) 67261
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "elec"] 2.246 s (5%) 84.361 ms 1.95 GiB (1%) 5333460
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 2.072 ms (5%) 5.68 MiB (1%) 11526
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "marine"] 2.752 ms (5%) 5.98 MiB (1%) 31590
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "polygon1"] 9.405 ms (5%) 23.60 MiB (1%) 32945
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "polygon3"] 34.736 ms (5%) 91.24 MiB (1%) 86881
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "robotarm"] 19.126 ms (5%) 51.98 MiB (1%) 51956
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "structural"] 1.549 ms (5%) 8.80 MiB (1%) 34276
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "camshape"] 880.458 ms (5%) 21.652 ms 319.06 MiB (1%) 1663699
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "catenary"] 228.271 ms (5%) 55.92 MiB (1%) 706259
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "chain"] 312.286 ms (5%) 66.73 MiB (1%) 964177
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "channel"] 1.583 s (5%) 56.875 ms 275.27 MiB (1%) 4106719
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "clnlbeam"] 293.619 ms (5%) 67.81 MiB (1%) 836216
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "controlinvestment"] 255.463 ms (5%) 69.98 MiB (1%) 843549
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "elec"] 476.984 s (5%) 7.171 s 36.47 GiB (1%) 108440280
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "hovercraft1d"] 20.802 ms (5%) 10.87 MiB (1%) 110151
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "marine"] 187.112 ms (5%) 44.58 MiB (1%) 520574
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon1"] 115.309 ms (5%) 32.13 MiB (1%) 377766
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon3"] 405.573 ms (5%) 142.87 MiB (1%) 1007339
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "robotarm"] 334.377 ms (5%) 99.67 MiB (1%) 872959
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "structural"] 224.497 ms (5%) 150.37 MiB (1%) 475483

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["hess_coord", "optimized", "Float64", "scalable_cons", "sparse"]
  • ["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse"]
  • ["hessian_backend", "optimized", "Float64", "scalable", "sparse"]
  • ["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics"]

Julia versioninfo

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      18625 s          0 s        913 s      58599 s          0 s
       #2     0 MHz      30170 s          0 s        884 s      47067 s          0 s
       #3     0 MHz      17032 s          0 s       1020 s      60082 s          0 s
       #4     0 MHz      27003 s          0 s        956 s      50182 s          0 s
  Memory: 15.620769500732422 GB (12145.01171875 MB free)
  Uptime: 7828.58 sec
  Load Avg:  1.09  1.05  1.01
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Baseline result

Benchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jl

Job Properties

  • Time of benchmark: 7 Jun 2025 - 03:28
  • Package commit: fd0d248
  • Julia commit: 760b2e5
  • Julia command flags: None
  • Environment variables: None

Results

Below is a table of this job's results, obtained by running the benchmarks.
The values listed in the ID column have the structure [parent_group, child_group, ..., key], and can be used to
index into the BaseBenchmarks suite to retrieve the corresponding benchmarks.
The percentages accompanying time and memory values in the below table are noise tolerances. The "true"
time/memory value for a given benchmark is expected to fall within this percentage of the reported value.
An empty cell means that the value was zero.

ID time GC time memory allocations
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "camshape"] 406.519 ms (5%) 1.61 MiB (1%) 12348
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "catenary"] 13.099 ms (5%) 356.98 KiB (1%) 2390
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "chain"] 23.482 ms (5%) 275.29 KiB (1%) 1932
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "channel"] 808.682 ms (5%) 974.16 KiB (1%) 6742
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "clnlbeam"] 13.745 ms (5%) 120.85 KiB (1%) 802
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "controlinvestment"] 36.731 ms (5%) 275.29 KiB (1%) 1932
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "elec"] 910.639 s (5%) 352.555 ms 113.93 MiB (1%) 793214
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "hovercraft1d"] 540.799 μs (5%) 5.57 MiB (1%) 472
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "marine"] 367.912 ms (5%) 4.18 MiB (1%) 30600
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "polygon1"] 18.997 ms (5%) 206.63 KiB (1%) 1280
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "polygon3"] 74.139 ms (5%) 614.23 KiB (1%) 4406
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "robotarm"] 78.821 ms (5%) 810.79 KiB (1%) 5896
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "structural"] 13.773 ms (5%) 92.39 KiB (1%) 854
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglina"] 48.602 ms (5%) 328.33 KiB (1%) 2465
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglinb"] 46.261 ms (5%) 328.33 KiB (1%) 2465
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "bdqrtic"] 74.644 ms (5%) 335.41 KiB (1%) 2461
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brownal"] 18.643 s (5%) 23.354 ms 197.78 MiB (1%) 1466005
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "broyden3d"] 23.963 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brybnd"] 67.506 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "dixon3dq"] 9.111 ms (5%) 201.23 KiB (1%) 1469
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "errinros_mod"] 63.728 ms (5%) 336.18 KiB (1%) 2467
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "freuroth"] 75.116 ms (5%) 336.18 KiB (1%) 2467
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "hovercraft1d"] 1.679 ms (5%) 115.48 KiB (1%) 797
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "integreq"] 18.446 s (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "morebv"] 34.647 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "penalty1"] 19.828 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "power"] 2.855 ms (5%) 81.23 KiB (1%) 469
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "sbrybnd"] 95.152 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "spmsrtls"] 376.863 ms (5%) 1.82 MiB (1%) 13965
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "tquartic"] 12.085 ms (5%) 208.32 KiB (1%) 1465
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "camshape"] 19.414 ms (5%) 54.68 MiB (1%) 92727
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "catenary"] 6.902 ms (5%) 18.06 MiB (1%) 31374
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "chain"] 6.582 ms (5%) 13.33 MiB (1%) 40181
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "channel"] 20.528 ms (5%) 49.63 MiB (1%) 128020
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 6.536 ms (5%) 13.93 MiB (1%) 43420
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "controlinvestment"] 18.097 ms (5%) 45.43 MiB (1%) 67262
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "elec"] 2.238 s (5%) 78.105 ms 1.95 GiB (1%) 5333461
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 2.083 ms (5%) 5.68 MiB (1%) 11517
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "marine"] 2.728 ms (5%) 5.98 MiB (1%) 31591
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "polygon1"] 9.390 ms (5%) 23.60 MiB (1%) 32946
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "polygon3"] 34.671 ms (5%) 91.24 MiB (1%) 86882
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "robotarm"] 19.073 ms (5%) 51.98 MiB (1%) 51957
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "structural"] 1.536 ms (5%) 8.80 MiB (1%) 34277
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "camshape"] 628.204 ms (5%) 21.287 ms 319.06 MiB (1%) 1663700
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "catenary"] 122.880 ms (5%) 55.92 MiB (1%) 706260
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "chain"] 151.388 ms (5%) 66.73 MiB (1%) 964178
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "channel"] 700.147 ms (5%) 275.27 MiB (1%) 4106715
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "clnlbeam"] 156.777 ms (5%) 67.75 MiB (1%) 835221
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "controlinvestment"] 133.352 ms (5%) 69.98 MiB (1%) 843550
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "elec"] 436.149 s (5%) 6.415 s 36.47 GiB (1%) 108440281
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "hovercraft1d"] 13.006 ms (5%) 10.87 MiB (1%) 110142
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "marine"] 97.600 ms (5%) 44.58 MiB (1%) 520575
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon1"] 56.260 ms (5%) 32.13 MiB (1%) 377767
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon3"] 243.285 ms (5%) 142.87 MiB (1%) 1007340
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "robotarm"] 180.923 ms (5%) 99.67 MiB (1%) 872960
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "structural"] 157.267 ms (5%) 150.37 MiB (1%) 475484

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["hess_coord", "optimized", "Float64", "scalable_cons", "sparse"]
  • ["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse"]
  • ["hessian_backend", "optimized", "Float64", "scalable", "sparse"]
  • ["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics"]

Julia versioninfo

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      26469 s          0 s       1248 s      85858 s          0 s
       #2     0 MHz      45381 s          0 s       1212 s      66982 s          0 s
       #3     0 MHz      24593 s          0 s       1408 s      87578 s          0 s
       #4     0 MHz      35849 s          0 s       1344 s      76396 s          0 s
  Memory: 15.620769500732422 GB (12422.8828125 MB free)
  Uptime: 11376.3 sec
  Load Avg:  1.0  1.02  1.0
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Runtime information

Runtime Info
BLAS #threads 2
BLAS.vendor() lbt
Sys.CPU_THREADS 4

lscpu output:

Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        48 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               4
On-line CPU(s) list:                  0-3
Vendor ID:                            AuthenticAMD
Model name:                           AMD EPYC 7763 64-Core Processor
CPU family:                           25
Model:                                1
Thread(s) per core:                   2
Core(s) per socket:                   2
Socket(s):                            1
Stepping:                             1
BogoMIPS:                             4890.85
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves user_shstk clzero xsaveerptr rdpru arat npt nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload umip vaes vpclmulqdq rdpid fsrm
Virtualization:                       AMD-V
Hypervisor vendor:                    Microsoft
Virtualization type:                  full
L1d cache:                            64 KiB (2 instances)
L1i cache:                            64 KiB (2 instances)
L2 cache:                             1 MiB (2 instances)
L3 cache:                             32 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-3
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Vulnerable: Safe RET, no microcode
Vulnerability Spec store bypass:      Vulnerable
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Retpolines; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected
Cpu Property Value
Brand AMD EPYC 7763 64-Core Processor
Vendor :AMD
Architecture :Unknown
Model Family: 0xaf, Model: 0x01, Stepping: 0x01, Type: 0x00
Cores 16 physical cores, 16 logical cores (on executing CPU)
No Hyperthreading hardware capability detected
Clock Frequencies Not supported by CPU
Data Cache Level 1:3 : (32, 512, 32768) kbytes
64 byte cache line size
Address Size 48 bits virtual, 48 bits physical
SIMD 256 bit = 32 byte max. SIMD vector size
Time Stamp Counter TSC is accessible via rdtsc
TSC runs at constant rate (invariant from clock frequency)
Perf. Monitoring Performance Monitoring Counters (PMC) are not supported
Hypervisor Yes, Microsoft

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Benchmark result

Judge result

Benchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jl

Job Properties

  • Time of benchmarks:
    • Target: 7 Jun 2025 - 02:29
    • Baseline: 7 Jun 2025 - 03:31
  • Package commits:
  • Julia commits:
    • Target: 760b2e5
    • Baseline: 760b2e5
  • Julia command flags:
    • Target: None
    • Baseline: None
  • Environment variables:
    • Target: None
    • Baseline: None

Results

A ratio greater than 1.0 denotes a possible regression (marked with ❌), while a ratio less
than 1.0 denotes a possible improvement (marked with ✅). Brackets display tolerances for the benchmark estimates. Only significant results - results
that indicate possible regressions or improvements - are shown below (thus, an empty table means that all
benchmark results remained invariant between builds).

ID time ratio memory ratio
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "channel"] 0.92 (5%) ✅ 1.00 (1%)
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brownal"] 0.86 (5%) ✅ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "camshape"] 1.24 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "catenary"] 1.78 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "chain"] 1.89 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "channel"] 2.04 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "clnlbeam"] 1.71 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "controlinvestment"] 1.67 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "elec"] 1.10 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "hovercraft1d"] 1.71 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "marine"] 1.76 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon1"] 1.66 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon3"] 1.52 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "robotarm"] 1.76 (5%) ❌ 1.00 (1%)
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "structural"] 1.23 (5%) ❌ 1.00 (1%)

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["hess_coord", "optimized", "Float64", "scalable_cons", "sparse"]
  • ["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse"]
  • ["hessian_backend", "optimized", "Float64", "scalable", "sparse"]
  • ["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics"]

Julia versioninfo

Target

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      17183 s          4 s        938 s      60426 s          0 s
       #2     0 MHz      34732 s          0 s        856 s      42963 s          0 s
       #3     0 MHz      16945 s          0 s       1052 s      60542 s          0 s
       #4     0 MHz      23985 s          0 s        948 s      53592 s          0 s
  Memory: 15.620765686035156 GB (12497.8828125 MB free)
  Uptime: 7869.29 sec
  Load Avg:  1.01  1.02  1.0
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Baseline

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      25388 s          4 s       1293 s      88709 s          0 s
       #2     0 MHz      50978 s          0 s       1194 s      63234 s          0 s
       #3     0 MHz      23406 s          0 s       1462 s      90517 s          0 s
       #4     0 MHz      33844 s          0 s       1340 s      80194 s          0 s
  Memory: 15.620765686035156 GB (12660.203125 MB free)
  Uptime: 11557.4 sec
  Load Avg:  1.05  1.03  1.0
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Target result

Benchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jl

Job Properties

  • Time of benchmark: 7 Jun 2025 - 02:29
  • Package commit: 6ab12a2
  • Julia commit: 760b2e5
  • Julia command flags: None
  • Environment variables: None

Results

Below is a table of this job's results, obtained by running the benchmarks.
The values listed in the ID column have the structure [parent_group, child_group, ..., key], and can be used to
index into the BaseBenchmarks suite to retrieve the corresponding benchmarks.
The percentages accompanying time and memory values in the below table are noise tolerances. The "true"
time/memory value for a given benchmark is expected to fall within this percentage of the reported value.
An empty cell means that the value was zero.

ID time GC time memory allocations
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "camshape"] 407.376 ms (5%) 1.61 MiB (1%) 12348
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "catenary"] 13.064 ms (5%) 356.98 KiB (1%) 2390
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "chain"] 23.373 ms (5%) 275.29 KiB (1%) 1932
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "channel"] 814.608 ms (5%) 974.16 KiB (1%) 6742
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "clnlbeam"] 14.024 ms (5%) 120.85 KiB (1%) 802
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "controlinvestment"] 36.259 ms (5%) 275.29 KiB (1%) 1932
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "elec"] 911.748 s (5%) 379.712 ms 113.93 MiB (1%) 793214
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "hovercraft1d"] 581.784 μs (5%) 5.57 MiB (1%) 472
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "marine"] 360.174 ms (5%) 4.18 MiB (1%) 30600
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "polygon1"] 19.068 ms (5%) 206.63 KiB (1%) 1280
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "polygon3"] 74.119 ms (5%) 614.23 KiB (1%) 4406
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "robotarm"] 78.893 ms (5%) 810.79 KiB (1%) 5896
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "structural"] 13.916 ms (5%) 92.39 KiB (1%) 854
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglina"] 47.899 ms (5%) 328.33 KiB (1%) 2465
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglinb"] 46.555 ms (5%) 328.33 KiB (1%) 2465
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "bdqrtic"] 76.968 ms (5%) 335.41 KiB (1%) 2461
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brownal"] 18.476 s (5%) 23.817 ms 197.78 MiB (1%) 1466005
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "broyden3d"] 23.923 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brybnd"] 67.520 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "dixon3dq"] 8.895 ms (5%) 201.23 KiB (1%) 1469
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "errinros_mod"] 64.298 ms (5%) 336.18 KiB (1%) 2467
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "freuroth"] 79.783 ms (5%) 336.18 KiB (1%) 2467
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "hovercraft1d"] 1.731 ms (5%) 115.48 KiB (1%) 797
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "integreq"] 16.529 s (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "morebv"] 34.698 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "penalty1"] 19.030 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "power"] 2.910 ms (5%) 81.23 KiB (1%) 469
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "sbrybnd"] 95.148 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "spmsrtls"] 365.613 ms (5%) 1.82 MiB (1%) 13965
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "tquartic"] 12.300 ms (5%) 208.32 KiB (1%) 1465
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "camshape"] 19.775 ms (5%) 54.68 MiB (1%) 92726
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "catenary"] 7.021 ms (5%) 18.06 MiB (1%) 31373
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "chain"] 6.687 ms (5%) 13.33 MiB (1%) 40180
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "channel"] 20.865 ms (5%) 49.63 MiB (1%) 128019
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 6.624 ms (5%) 13.93 MiB (1%) 43419
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "controlinvestment"] 18.488 ms (5%) 45.43 MiB (1%) 67261
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "elec"] 2.187 s (5%) 86.585 ms 1.95 GiB (1%) 5333460
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 2.115 ms (5%) 5.68 MiB (1%) 11516
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "marine"] 2.800 ms (5%) 5.98 MiB (1%) 31590
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "polygon1"] 9.608 ms (5%) 23.60 MiB (1%) 32945
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "polygon3"] 35.320 ms (5%) 91.24 MiB (1%) 86881
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "robotarm"] 19.395 ms (5%) 51.98 MiB (1%) 51956
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "structural"] 1.576 ms (5%) 8.80 MiB (1%) 34276
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "camshape"] 781.427 ms (5%) 20.542 ms 319.06 MiB (1%) 1663699
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "catenary"] 217.872 ms (5%) 55.92 MiB (1%) 706259
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "chain"] 281.807 ms (5%) 66.73 MiB (1%) 964177
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "channel"] 1.405 s (5%) 55.947 ms 275.27 MiB (1%) 4106714
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "clnlbeam"] 260.753 ms (5%) 67.81 MiB (1%) 836216
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "controlinvestment"] 222.276 ms (5%) 69.98 MiB (1%) 843549
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "elec"] 517.099 s (5%) 6.992 s 36.47 GiB (1%) 108440280
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "hovercraft1d"] 22.066 ms (5%) 10.87 MiB (1%) 110141
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "marine"] 172.922 ms (5%) 44.58 MiB (1%) 520574
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon1"] 92.120 ms (5%) 32.13 MiB (1%) 377766
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon3"] 371.136 ms (5%) 142.87 MiB (1%) 1007339
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "robotarm"] 318.873 ms (5%) 99.67 MiB (1%) 872959
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "structural"] 202.809 ms (5%) 150.37 MiB (1%) 475483

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["hess_coord", "optimized", "Float64", "scalable_cons", "sparse"]
  • ["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse"]
  • ["hessian_backend", "optimized", "Float64", "scalable", "sparse"]
  • ["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics"]

Julia versioninfo

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      17183 s          4 s        938 s      60426 s          0 s
       #2     0 MHz      34732 s          0 s        856 s      42963 s          0 s
       #3     0 MHz      16945 s          0 s       1052 s      60542 s          0 s
       #4     0 MHz      23985 s          0 s        948 s      53592 s          0 s
  Memory: 15.620765686035156 GB (12497.8828125 MB free)
  Uptime: 7869.29 sec
  Load Avg:  1.01  1.02  1.0
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Baseline result

Benchmark Report for /home/runner/work/ADNLPModels.jl/ADNLPModels.jl

Job Properties

  • Time of benchmark: 7 Jun 2025 - 03:31
  • Package commit: fd0d248
  • Julia commit: 760b2e5
  • Julia command flags: None
  • Environment variables: None

Results

Below is a table of this job's results, obtained by running the benchmarks.
The values listed in the ID column have the structure [parent_group, child_group, ..., key], and can be used to
index into the BaseBenchmarks suite to retrieve the corresponding benchmarks.
The percentages accompanying time and memory values in the below table are noise tolerances. The "true"
time/memory value for a given benchmark is expected to fall within this percentage of the reported value.
An empty cell means that the value was zero.

ID time GC time memory allocations
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "camshape"] 407.872 ms (5%) 1.61 MiB (1%) 12348
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "catenary"] 13.111 ms (5%) 356.98 KiB (1%) 2390
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "chain"] 23.620 ms (5%) 275.29 KiB (1%) 1932
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "channel"] 889.543 ms (5%) 974.16 KiB (1%) 6742
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "clnlbeam"] 13.798 ms (5%) 120.85 KiB (1%) 802
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "controlinvestment"] 36.708 ms (5%) 275.29 KiB (1%) 1932
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "elec"] 911.022 s (5%) 365.088 ms 113.93 MiB (1%) 793214
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "hovercraft1d"] 596.032 μs (5%) 5.57 MiB (1%) 472
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "marine"] 361.159 ms (5%) 4.18 MiB (1%) 30600
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "polygon1"] 19.187 ms (5%) 206.63 KiB (1%) 1280
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "polygon3"] 73.891 ms (5%) 614.23 KiB (1%) 4406
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "robotarm"] 80.490 ms (5%) 810.79 KiB (1%) 5896
["hess_coord", "optimized", "Float64", "scalable_cons", "sparse", "structural"] 13.817 ms (5%) 92.39 KiB (1%) 854
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglina"] 48.462 ms (5%) 328.33 KiB (1%) 2465
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "arglinb"] 46.109 ms (5%) 328.33 KiB (1%) 2465
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "bdqrtic"] 74.998 ms (5%) 335.41 KiB (1%) 2461
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brownal"] 21.407 s (5%) 21.277 ms 197.78 MiB (1%) 1466005
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "broyden3d"] 23.912 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "brybnd"] 70.048 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "dixon3dq"] 9.358 ms (5%) 201.23 KiB (1%) 1469
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "errinros_mod"] 64.094 ms (5%) 336.18 KiB (1%) 2467
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "freuroth"] 77.271 ms (5%) 336.18 KiB (1%) 2467
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "hovercraft1d"] 1.726 ms (5%) 115.48 KiB (1%) 797
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "integreq"] 16.501 s (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "morebv"] 34.788 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "penalty1"] 19.821 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "power"] 2.917 ms (5%) 81.23 KiB (1%) 469
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "sbrybnd"] 96.731 ms (5%) 209.09 KiB (1%) 1471
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "spmsrtls"] 369.517 ms (5%) 1.82 MiB (1%) 13965
["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse", "tquartic"] 12.144 ms (5%) 208.32 KiB (1%) 1465
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "camshape"] 19.943 ms (5%) 54.68 MiB (1%) 92727
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "catenary"] 7.111 ms (5%) 18.06 MiB (1%) 31374
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "chain"] 6.691 ms (5%) 13.33 MiB (1%) 40181
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "channel"] 20.759 ms (5%) 49.63 MiB (1%) 128020
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "clnlbeam"] 6.661 ms (5%) 13.93 MiB (1%) 43420
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "controlinvestment"] 18.759 ms (5%) 45.43 MiB (1%) 67262
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "elec"] 2.195 s (5%) 82.047 ms 1.95 GiB (1%) 5333461
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "hovercraft1d"] 2.171 ms (5%) 5.68 MiB (1%) 11517
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "marine"] 2.739 ms (5%) 5.98 MiB (1%) 31591
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "polygon1"] 9.714 ms (5%) 23.60 MiB (1%) 32946
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "polygon3"] 35.412 ms (5%) 91.24 MiB (1%) 86882
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "robotarm"] 19.457 ms (5%) 51.98 MiB (1%) 51945
["hessian_backend", "optimized", "Float64", "scalable", "sparse", "structural"] 1.602 ms (5%) 8.80 MiB (1%) 34277
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "camshape"] 627.936 ms (5%) 22.461 ms 319.06 MiB (1%) 1663700
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "catenary"] 122.732 ms (5%) 55.92 MiB (1%) 706260
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "chain"] 149.155 ms (5%) 66.73 MiB (1%) 964178
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "channel"] 686.953 ms (5%) 275.27 MiB (1%) 4106715
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "clnlbeam"] 152.842 ms (5%) 67.75 MiB (1%) 835221
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "controlinvestment"] 132.873 ms (5%) 69.98 MiB (1%) 843550
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "elec"] 470.791 s (5%) 6.415 s 36.47 GiB (1%) 108440281
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "hovercraft1d"] 12.908 ms (5%) 10.87 MiB (1%) 110142
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "marine"] 98.280 ms (5%) 44.58 MiB (1%) 520575
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon1"] 55.563 ms (5%) 32.04 MiB (1%) 376267
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "polygon3"] 243.885 ms (5%) 142.87 MiB (1%) 1007340
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "robotarm"] 180.813 ms (5%) 99.67 MiB (1%) 872948
["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics", "structural"] 164.242 ms (5%) 150.37 MiB (1%) 475484

Benchmark Group List

Here's a list of all the benchmark groups executed by this job:

  • ["hess_coord", "optimized", "Float64", "scalable_cons", "sparse"]
  • ["hess_coord_residual", "optimized", "Float64", "scalable_nls", "sparse"]
  • ["hessian_backend", "optimized", "Float64", "scalable", "sparse"]
  • ["hessian_backend", "optimized", "Float64", "scalable", "sparse_symbolics"]

Julia versioninfo

Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
      Ubuntu 24.04.2 LTS
  uname: Linux 6.11.0-1015-azure #15~24.04.1-Ubuntu SMP Thu May  1 02:52:08 UTC 2025 x86_64 x86_64
  CPU: AMD EPYC 7763 64-Core Processor: 
              speed         user         nice          sys         idle          irq
       #1     0 MHz      25388 s          4 s       1293 s      88709 s          0 s
       #2     0 MHz      50978 s          0 s       1194 s      63234 s          0 s
       #3     0 MHz      23406 s          0 s       1462 s      90517 s          0 s
       #4     0 MHz      33844 s          0 s       1340 s      80194 s          0 s
  Memory: 15.620765686035156 GB (12660.203125 MB free)
  Uptime: 11557.4 sec
  Load Avg:  1.05  1.03  1.0
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

Runtime information

Runtime Info
BLAS #threads 2
BLAS.vendor() lbt
Sys.CPU_THREADS 4

lscpu output:

Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        48 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               4
On-line CPU(s) list:                  0-3
Vendor ID:                            AuthenticAMD
Model name:                           AMD EPYC 7763 64-Core Processor
CPU family:                           25
Model:                                1
Thread(s) per core:                   2
Core(s) per socket:                   2
Socket(s):                            1
Stepping:                             1
BogoMIPS:                             4890.85
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves user_shstk clzero xsaveerptr rdpru arat npt nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload umip vaes vpclmulqdq rdpid fsrm
Virtualization:                       AMD-V
Hypervisor vendor:                    Microsoft
Virtualization type:                  full
L1d cache:                            64 KiB (2 instances)
L1i cache:                            64 KiB (2 instances)
L2 cache:                             1 MiB (2 instances)
L3 cache:                             32 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-3
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Vulnerable: Safe RET, no microcode
Vulnerability Spec store bypass:      Vulnerable
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Retpolines; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected
Cpu Property Value
Brand AMD EPYC 7763 64-Core Processor
Vendor :AMD
Architecture :Unknown
Model Family: 0xaf, Model: 0x01, Stepping: 0x01, Type: 0x00
Cores 16 physical cores, 16 logical cores (on executing CPU)
No Hyperthreading hardware capability detected
Clock Frequencies Not supported by CPU
Data Cache Level 1:3 : (32, 512, 32768) kbytes
64 byte cache line size
Address Size 48 bits virtual, 48 bits physical
SIMD 256 bit = 32 byte max. SIMD vector size
Time Stamp Counter TSC is accessible via rdtsc
TSC runs at constant rate (invariant from clock frequency)
Perf. Monitoring Performance Monitoring Counters (PMC) are not supported
Hypervisor Yes, Microsoft

@jbcaillau
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@amontoison making progress 🙂🤞🏽

@amontoison
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@jbcaillau The problem is deeper than expected, ReverseDiff.jl calls ForwardDiff.jl internally sometimes and it is when it breaks your code. I probably need to overload a few functions in ReverseDiff.jl to fix your issue.

@jbcaillau
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thanks for the update. are we the only one with such an issue when doing forward over reverse?

@amontoison
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To the best of my knowledge, yes you are the only one concerned by this issue.
I should also check the function that you generate in OC.jl to see if anything is wrong.
What is the easy way to extract the f and c! that you generate?

@jbcaillau
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jbcaillau commented Jun 8, 2025 •
edited
Loading

@amontoison under the control of @PierreMartinon: the nlp returned by direct_transcription below is ADNLPModel with standard access to both objective and constraints (check its construction there).

using OptimalControl
using NLPModelsIpopt

x0 = [ 0.
       1. ]
A = [  0. 1.
      -1. 0. ]
B = [ 0.
      1. ]
Q = [ 1. 0.
      0. 1. ]
R = 1.
tf = 3.

ocp = @def begin
    t ∈ [0, tf], time
    x ∈ R², state
    u ∈ R, control
    x(0) == x0
    ẋ(t) == A * x(t) + B * u(t)
    0.5∫( x(t)' * Q * x(t) + u(t)' * R * u(t) ) → min
end

docp, nlp = direct_transcription(ocp)

solve(ocp) # error "Cannot determine ordering of Dual tags ForwardDiff.Tag{ReverseDiff.var..."
solve(ocp; adnlp_backend = :default) # no error

@tmigot
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tmigot commented Jun 30, 2025

What is the status here? It doesn't seem right tbh.

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3 participants
@amontoison @jbcaillau @tmigot