[MadNLPGPU] Upgrade CUDSS -- support iterative refinement and hybrid mode #329

amontoison · 2024-04-19T21:25:16Z

No description provided.

lib/MadNLPGPU/src/cudss.jl

…mode

amontoison · 2024-07-05T04:31:10Z

amontoison · 2024-07-05T04:53:58Z

I tested on my cluster and I have a few tests that are failing.
They are not related to this PR.

Error During Test at /home/montalex/.julia/packages/MadNLPTests/kA3ek/src/MadNLPTests.jl:139
  Got exception outside of a @test
  type CuSparseMatrixCSC has no field nzval
  Stacktrace:
    [1] getproperty
      @ ./Base.jl:37 [inlined]
    [2] initialize!(kkt::MadNLP.SparseCondensedKKTSystem{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CUDA.CUSPARSE.CuSparseMatrixCSC{Float64, Int32}, MadNLP.ExactHessian{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}}, LapackGPUSolver{Float64}, CuArray{Int64, 1, CUDA.DeviceMemory}, CuArray{Int32, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Int32}, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Tuple{Int64, Int64, Int64}}, 1, CUDA.DeviceMemory}, @NamedTuple{jptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, hess_com_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, hess_com_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, jt_csc_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, jt_csc_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, diag_map_to::CuArray{Int32, 1, CUDA.DeviceMemory}, diag_map_fr::CuArray{Int32, 1, CUDA.DeviceMemory}}})
      @ MadNLP ~/.julia/packages/MadNLP/u0fX5/src/KKT/sparse.jl:426
    [3] initialize!(solver::MadNLPSolver{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CuArray{Int64, 1, CUDA.DeviceMemory}, MadNLP.SparseCondensedKKTSystem{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CUDA.CUSPARSE.CuSparseMatrixCSC{Float64, Int32}, MadNLP.ExactHessian{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}}, LapackGPUSolver{Float64}, CuArray{Int64, 1, CUDA.DeviceMemory}, CuArray{Int32, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Int32}, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Tuple{Int64, Int64, Int64}}, 1, CUDA.DeviceMemory}, @NamedTuple{jptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, hess_com_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, hess_com_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, jt_csc_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, jt_csc_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, diag_map_to::CuArray{Int32, 1, CUDA.DeviceMemory}, diag_map_fr::CuArray{Int32, 1, CUDA.DeviceMemory}}}, MadNLPTests.SparseWrapperModel{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, Float64, Vector{Int64}, Vector{Float64}, NLPModelsJuMP.MathOptNLPModel}, MadNLP.SparseCallback{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CuArray{Int64, 1, CUDA.DeviceMemory}, MadNLPTests.SparseWrapperModel{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, Float64, Vector{Int64}, Vector{Float64}, NLPModelsJuMP.MathOptNLPModel}, MadNLP.RelaxBound, MadNLP.RelaxEquality}, MadNLP.RichardsonIterator{Float64, MadNLP.SparseCondensedKKTSystem{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CUDA.CUSPARSE.CuSparseMatrixCSC{Float64, Int32}, MadNLP.ExactHessian{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}}, LapackGPUSolver{Float64}, CuArray{Int64, 1, CUDA.DeviceMemory}, CuArray{Int32, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Int32}, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Tuple{Int64, Int64, Int64}}, 1, CUDA.DeviceMemory}, @NamedTuple{jptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, hess_com_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, hess_com_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, jt_csc_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, jt_csc_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, diag_map_to::CuArray{Int32, 1, CUDA.DeviceMemory}, diag_map_fr::CuArray{Int32, 1, CUDA.DeviceMemory}}}}, MadNLP.InertiaBased, MadNLP.UnreducedKKTVector{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CuArray{Int64, 1, CUDA.DeviceMemory}}})
      @ MadNLP ~/.julia/packages/MadNLP/u0fX5/src/IPM/solver.jl:60
    [4] solve!(nlp::MadNLPTests.SparseWrapperModel{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, Float64, Vector{Int64}, Vector{Float64}, NLPModelsJuMP.MathOptNLPModel}, solver::MadNLPSolver{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CuArray{Int64, 1, CUDA.DeviceMemory}, MadNLP.SparseCondensedKKTSystem{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CUDA.CUSPARSE.CuSparseMatrixCSC{Float64, Int32}, MadNLP.ExactHessian{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}}, LapackGPUSolver{Float64}, CuArray{Int64, 1, CUDA.DeviceMemory}, CuArray{Int32, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Int32}, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Tuple{Int64, Int64, Int64}}, 1, CUDA.DeviceMemory}, @NamedTuple{jptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, hess_com_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, hess_com_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, jt_csc_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, jt_csc_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, diag_map_to::CuArray{Int32, 1, CUDA.DeviceMemory}, diag_map_fr::CuArray{Int32, 1, CUDA.DeviceMemory}}}, MadNLPTests.SparseWrapperModel{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, Float64, Vector{Int64}, Vector{Float64}, NLPModelsJuMP.MathOptNLPModel}, MadNLP.SparseCallback{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CuArray{Int64, 1, CUDA.DeviceMemory}, MadNLPTests.SparseWrapperModel{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, Float64, Vector{Int64}, Vector{Float64}, NLPModelsJuMP.MathOptNLPModel}, MadNLP.RelaxBound, MadNLP.RelaxEquality}, MadNLP.RichardsonIterator{Float64, MadNLP.SparseCondensedKKTSystem{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CUDA.CUSPARSE.CuSparseMatrixCSC{Float64, Int32}, MadNLP.ExactHessian{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}}, LapackGPUSolver{Float64}, CuArray{Int64, 1, CUDA.DeviceMemory}, CuArray{Int32, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Int32}, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Tuple{Int64, Int64, Int64}}, 1, CUDA.DeviceMemory}, @NamedTuple{jptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, hess_com_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, hess_com_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, jt_csc_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, jt_csc_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, diag_map_to::CuArray{Int32, 1, CUDA.DeviceMemory}, diag_map_fr::CuArray{Int32, 1, CUDA.DeviceMemory}}}}, MadNLP.InertiaBased, MadNLP.UnreducedKKTVector{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CuArray{Int64, 1, CUDA.DeviceMemory}}}, stats::MadNLP.MadNLPExecutionStats{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}}; x::Nothing, y::Nothing, zl::Nothing, zu::Nothing, kwargs::@Kwargs{})
      @ MadNLP ~/.julia/packages/MadNLP/u0fX5/src/IPM/solver.jl:159
    [5] solve!
      @ ~/.julia/packages/MadNLP/u0fX5/src/IPM/solver.jl:128 [inlined]
    [6] solve!
      @ ~/.julia/packages/MadNLP/u0fX5/src/IPM/solver.jl:14 [inlined]
    [7] solve!(solver::MadNLPSolver{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CuArray{Int64, 1, CUDA.DeviceMemory}, MadNLP.SparseCondensedKKTSystem{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CUDA.CUSPARSE.CuSparseMatrixCSC{Float64, Int32}, MadNLP.ExactHessian{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}}, LapackGPUSolver{Float64}, CuArray{Int64, 1, CUDA.DeviceMemory}, CuArray{Int32, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Int32}, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Tuple{Int64, Int64, Int64}}, 1, CUDA.DeviceMemory}, @NamedTuple{jptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, hess_com_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, hess_com_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, jt_csc_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, jt_csc_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, diag_map_to::CuArray{Int32, 1, CUDA.DeviceMemory}, diag_map_fr::CuArray{Int32, 1, CUDA.DeviceMemory}}}, MadNLPTests.SparseWrapperModel{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, Float64, Vector{Int64}, Vector{Float64}, NLPModelsJuMP.MathOptNLPModel}, MadNLP.SparseCallback{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CuArray{Int64, 1, CUDA.DeviceMemory}, MadNLPTests.SparseWrapperModel{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, Float64, Vector{Int64}, Vector{Float64}, NLPModelsJuMP.MathOptNLPModel}, MadNLP.RelaxBound, MadNLP.RelaxEquality}, MadNLP.RichardsonIterator{Float64, MadNLP.SparseCondensedKKTSystem{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CUDA.CUSPARSE.CuSparseMatrixCSC{Float64, Int32}, MadNLP.ExactHessian{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}}, LapackGPUSolver{Float64}, CuArray{Int64, 1, CUDA.DeviceMemory}, CuArray{Int32, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Int32}, 1, CUDA.DeviceMemory}, CuArray{Tuple{Int32, Tuple{Int64, Int64, Int64}}, 1, CUDA.DeviceMemory}, @NamedTuple{jptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, hess_com_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, hess_com_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, jt_csc_ptr::CuArray{Tuple{Int64, Int64}, 1, CUDA.DeviceMemory}, jt_csc_ptrptr::CuArray{Int64, 1, CUDA.DeviceMemory}, diag_map_to::CuArray{Int32, 1, CUDA.DeviceMemory}, diag_map_fr::CuArray{Int32, 1, CUDA.DeviceMemory}}}}, MadNLP.InertiaBased, MadNLP.UnreducedKKTVector{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, CuArray{Int64, 1, CUDA.DeviceMemory}}})
      @ MadNLP ~/.julia/packages/MadNLP/u0fX5/src/IPM/solver.jl:17
    [8] madnlp(model::MadNLPTests.SparseWrapperModel{Float64, CuArray{Float64, 1, CUDA.DeviceMemory}, Float64, Vector{Int64}, Vector{Float64}, NLPModelsJuMP.MathOptNLPModel}; kwargs::@Kwargs{print_level::MadNLP.LogLevels, linear_solver::UnionAll, lapack_algorithm::MadNLP.LinearFactorization})
      @ MadNLP ~/.julia/packages/MadNLP/u0fX5/src/IPM/solver.jl:11
    [9] macro expansion
      @ ~/.julia/packages/MadNLPTests/kA3ek/src/MadNLPTests.jl:149 [inlined]
   [10] macro expansion
      @ ~/Applications/julia/julia-1.10.3/share/julia/stdlib/v1.10/Test/src/Test.jl:1577 [inlined]
   [11] unbounded(optimizer_constructor::var"#11#22"; Arr::Type)
      @ MadNLPTests ~/.julia/packages/MadNLPTests/kA3ek/src/MadNLPTests.jl:140
   [12] macro expansion
      @ ~/.julia/packages/MadNLPTests/kA3ek/src/MadNLPTests.jl:115 [inlined]
   [13] macro expansion
      @ ~/Applications/julia/julia-1.10.3/share/julia/stdlib/v1.10/Test/src/Test.jl:1577 [inlined]
   [14] test_madnlp(name::String, optimizer_constructor::Function, exclude::Vector{String}; Arr::Type)
      @ MadNLPTests ~/.julia/packages/MadNLPTests/kA3ek/src/MadNLPTests.jl:114
   [15] macro expansion
      @ ~/Argonne/MadNLP.jl/lib/MadNLPGPU/test/madnlpgpu_test.jl:106 [inlined]
   [16] macro expansion
      @ ~/Applications/julia/julia-1.10.3/share/julia/stdlib/v1.10/Test/src/Test.jl:1577 [inlined]
   [17] top-level scope
      @ ~/Argonne/MadNLP.jl/lib/MadNLPGPU/test/madnlpgpu_test.jl:102
   [18] include(fname::String)
      @ Base.MainInclude ./client.jl:489
   [19] macro expansion
      @ ~/Argonne/MadNLP.jl/lib/MadNLPGPU/test/runtests.jl:7 [inlined]
   [20] macro expansion
      @ ~/Applications/julia/julia-1.10.3/share/julia/stdlib/v1.10/Test/src/Test.jl:1577 [inlined]
   [21] top-level scope
      @ ~/Argonne/MadNLP.jl/lib/MadNLPGPU/test/runtests.jl:7
   [22] include(fname::String)
      @ Base.MainInclude ./client.jl:489
   [23] top-level scope
      @ none:6
   [24] eval
      @ ./boot.jl:385 [inlined]
   [25] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:291
   [26] _start()
      @ Base ./client.jl:552
Test Summary:                                                | Pass  Error  Total     Time
MadNLPGPU test                                               |  170     51    221  5m20.0s
  MadNLPGPU test                                             |    2     51     53  2m42.3s
    CUDSS                                                    |           5      5  1m19.8s
      infeasible                                             |           1      1  1m08.2s
      unbounded                                              |           1      1     0.6s
      lootsma                                                |           1      1     2.1s
      eigmina                                                |           1      1     2.1s
      lp_examodels_issue75                                   |           1      1     0.4s
    CUDSS-AMD                                                |           5      5     5.5s
      infeasible                                             |           1      1     0.5s
      unbounded                                              |           1      1     0.7s
      lootsma                                                |           1      1     0.3s
      eigmina                                                |           1      1     0.4s
      lp_examodels_issue75                                   |           1      1     0.3s
    CUDSS-METIS                                              |           5      5     5.3s
      infeasible                                             |           1      1     0.4s
      unbounded                                              |           1      1     0.3s
      lootsma                                                |           1      1     0.3s
      eigmina                                                |           1      1     0.4s
      lp_examodels_issue75                                   |           1      1     0.3s
    CUDSS-HYBRID                                             |           5      5     5.3s
      infeasible                                             |           1      1     0.6s
      unbounded                                              |           1      1     0.3s
      lootsma                                                |           1      1     0.4s
      eigmina                                                |           1      1     0.4s
      lp_examodels_issue75                                   |           1      1     0.3s
    CUSOLVERRF                                               |           5      5     9.7s
      infeasible                                             |           1      1     4.9s
      unbounded                                              |           1      1     0.4s
      lootsma                                                |           1      1     0.3s
      eigmina                                                |           1      1     0.4s
      lp_examodels_issue75                                   |           1      1     0.3s
    CUSOLVER-CHOLESKY                                        |           5      5    10.1s
      infeasible                                             |           1      1     5.5s
      unbounded                                              |           1      1     0.3s
      lootsma                                                |           1      1     0.3s
      eigmina                                                |           1      1     0.4s
      lp_examodels_issue75                                   |           1      1     0.3s
    GLU                                                      |           5      5     8.6s
      infeasible                                             |           1      1     3.9s
      unbounded                                              |           1      1     0.3s
      lootsma                                                |           1      1     0.3s
      eigmina                                                |           1      1     0.4s
      lp_examodels_issue75                                   |           1      1     0.3s
    LapackGPU-BUNCHKAUFMAN                                   |           5      5     8.8s
      infeasible                                             |           1      1     4.0s
      unbounded                                              |           1      1     0.3s
      lootsma                                                |           1      1     0.3s
      eigmina                                                |           1      1     0.4s
      lp_examodels_issue75                                   |           1      1     0.3s
    LapackGPU-LU                                             |           5      5     5.0s
      infeasible                                             |           1      1     0.3s
      unbounded                                              |           1      1     0.3s
      lootsma                                                |           1      1     0.4s
      eigmina                                                |           1      1     0.4s
      lp_examodels_issue75                                   |           1      1     0.3s
    LapackGPU-QR                                             |           5      5     5.0s
      infeasible                                             |           1      1     0.3s
      unbounded                                              |           1      1     0.4s
      lootsma                                                |           1      1     0.3s
      eigmina                                                |           1      1     0.4s
      lp_examodels_issue75                                   |           1      1     0.3s
    LapackGPU-CHOLESKY                                       |           1      1     2.8s
      unbounded                                              |           1      1     2.8s
  MadNLPGPU (MadNLP.DenseKKTSystem)                          |   60            60  1m44.8s
  MadNLPGPU (MadNLP.DenseCondensedKKTSystem)                 |   60            60    33.8s
  MadNLP: MadNLP.BFGS + MadNLP.DenseKKTSystem                |   12            12     4.1s
  MadNLP: MadNLP.BFGS + MadNLP.DenseCondensedKKTSystem       |   12            12     3.8s
  MadNLP: MadNLP.DampedBFGS + MadNLP.DenseKKTSystem          |   12            12     3.5s
  MadNLP: MadNLP.DampedBFGS + MadNLP.DenseCondensedKKTSystem |   12            12     3.8s
ERROR: LoadError: Some tests did not pass: 170 passed, 0 failed, 51 errored, 0 broken.
in expression starting at /home/montalex/Argonne/MadNLP.jl/lib/MadNLPGPU/test/runtests.jl:6
ERROR: Package MadNLPGPU errored during testing

frapac · 2024-07-15T16:11:31Z

@amontoison Tests for MadNLPGPU are passing locally on my machine. I am not sure to understand why moonshot cannot find CUDSS.jl 0.3.1 there.

amontoison · 2024-07-15T17:26:54Z

@amontoison Tests for MadNLPGPU are passing locally on my machine. I am not sure to understand why moonshot cannot find CUDSS.jl 0.3.1 there.

I restarted the tests.

codecov-commenter · 2024-07-15T17:42:18Z

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@@           Coverage Diff           @@
##           master     #329   +/-   ##
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  Coverage   70.17%   70.17%           
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frapac · 2024-07-15T18:41:31Z

Thank you Alexis!

amontoison commented Apr 19, 2024

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lib/MadNLPGPU/src/cudss.jl Outdated Show resolved Hide resolved

amontoison mentioned this pull request Apr 24, 2024

CUDSS internal error (invalid argument: inertia correction) #333

Closed

sshin23 force-pushed the master branch from b1b39b9 to 1d93449 Compare May 17, 2024 14:29

amontoison changed the title ~~[MadNLPGPU] Upgrade CUDSS and support iterative refinement~~ [MadNLPGPU] Upgrade CUDSS -- support iterative refinement and hybrid mode Jul 5, 2024

[MadNLPGPU] Upgrade CUDSS -- support iterative refinement and hybrid …

65e334a

…mode

amontoison force-pushed the cudss_update branch from 0a4a24a to 65e334a Compare July 5, 2024 04:30

frapac mentioned this pull request Jul 15, 2024

CompatHelper: bump compat for CUDSS to 0.3 for package MadNLPGPU, (keep existing compat) #355

Closed

frapac approved these changes Jul 15, 2024

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amontoison closed this Jul 15, 2024

amontoison reopened this Jul 15, 2024

frapac merged commit dbfc0fc into MadNLP:master Jul 15, 2024
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amontoison deleted the cudss_update branch July 15, 2024 19:30

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[MadNLPGPU] Upgrade CUDSS -- support iterative refinement and hybrid mode #329

[MadNLPGPU] Upgrade CUDSS -- support iterative refinement and hybrid mode #329

amontoison commented Apr 19, 2024

amontoison commented Jul 5, 2024

amontoison commented Jul 5, 2024

frapac commented Jul 15, 2024

amontoison commented Jul 15, 2024

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frapac commented Jul 15, 2024

[MadNLPGPU] Upgrade CUDSS -- support iterative refinement and hybrid mode #329

[MadNLPGPU] Upgrade CUDSS -- support iterative refinement and hybrid mode #329

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amontoison commented Apr 19, 2024

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