PETSc artifact with MUMPS

[pmartorell]

@JordiManyer

Within the current version of GridapPETSc v0.5.2, it is not possible to use MUMPS without compiling PETSc in the local machine.

GridapPETSc points to PETSc_jll v3.15.2 that is not compiled with MUMPS. However, newer versions of this artifact already contain MUMPS on their dependencies; see PETSc_jll v3.18.8.

This is not an urgent issue, but it will help new users and simplify the pipelines of the packages that depend on GridapPETSc.

FYI @principejavier

[JordiManyer]

See this #99 . Help is welcome... We've tried and failed.

[lamBOOO]

Any news on this? I would need PETSc_jll on the Apple M4, which is not availble PETSc-v3.15.2.

I tried to look into it, but on my machine, the tests don't run (maybe I do somehting wrong).

I cloned the repo and used the following

docker-compose.yml

# use docker to get PETSc_jll working
version: "3.8"
services:
  julia:
    image: julia:1.9
    container_name: julia_container
    volumes:
      - .:/shared
    working_dir: /app
    tty: true

then did docker compose run julia, moved ; cd /shared and executed ] activate .. Then I typed ] test and got the following errors:

Details

   Installed Parameters ─────────── v0.12.3
   Installed UnPack ─────────────── v1.0.2
   Installed PolynomialBases ────── v0.4.22
   Installed LightXML ───────────── v0.9.1
   Installed Distances ──────────── v0.10.12
   Installed ArrayLayouts ───────── v1.11.0
   Installed CodecZlib ──────────── v0.7.7
   Installed FiniteDiff ─────────── v2.27.0
   Installed DocStringExtensions ── v0.9.3
  Downloaded artifact: MPICH
  Downloaded artifact: oneTBB
  Downloaded artifact: XML2
  Downloaded artifact: PETSc
  Downloaded artifact: Hwloc
  Downloaded artifact: Libiconv
  Downloaded artifact: OpenBLAS32
  Downloaded artifact: FFTW
  Downloaded artifact: OpenSpecFun
     Testing GridapPETSc
┌ Warning: Could not use exact versions of packages in manifest, re-resolving
└ @ Pkg.Operations /usr/local/julia/share/julia/stdlib/v1.9/Pkg/src/Operations.jl:1814
      Status `/tmp/jl_OIgqzU/Project.toml`
  [56d4f2e9] Gridap v0.18.9
  [f9701e48] GridapDistributed v0.4.6
  [bcdc36c2] GridapPETSc v0.5.3 `/shared`
  [da04e1cc] MPI v0.20.22
⌅ [5a9dfac6] PartitionedArrays v0.3.4
  [a0a7dd2c] SparseMatricesCSR v0.6.8
⌅ [8fa3689e] PETSc_jll v3.15.2+0
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [9a3f8284] Random
  [2f01184e] SparseArrays
  [8dfed614] Test
      Status `/tmp/jl_OIgqzU/Manifest.toml`
  [621f4979] AbstractFFTs v1.5.0
  [1520ce14] AbstractTrees v0.4.5
  [79e6a3ab] Adapt v4.1.1
  [dce04be8] ArgCheck v2.4.0
⌅ [4fba245c] ArrayInterface v7.7.1
⌅ [4c555306] ArrayLayouts v1.10.4
  [15f4f7f2] AutoHashEquals v2.2.0
  [fbb218c0] BSON v0.3.9
⌅ [8e7c35d0] BlockArrays v1.2.0
  [7a955b69] CircularArrays v1.4.0
  [944b1d66] CodecZlib v0.7.7
  [861a8166] Combinatorics v1.0.2
  [bbf7d656] CommonSubexpressions v0.3.1
  [34da2185] Compat v4.16.0
  [187b0558] ConstructionBase v1.5.8
  [864edb3b] DataStructures v0.18.20
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [b4f34e82] Distances v0.10.12
  [ffbed154] DocStringExtensions v0.9.3
  [7a1cc6ca] FFTW v1.8.1
  [442a2c76] FastGaussQuadrature v1.0.2
  [5789e2e9] FileIO v1.16.6
  [1a297f60] FillArrays v1.13.0
⌅ [6a86dc24] FiniteDiff v2.22.0
  [f6369f11] ForwardDiff v0.10.38
  [56d4f2e9] Gridap v0.18.9
  [f9701e48] GridapDistributed v0.4.6
  [bcdc36c2] GridapPETSc v0.5.3 `/shared`
  [92d709cd] IrrationalConstants v0.2.4
  [42fd0dbc] IterativeSolvers v0.9.4
  [033835bb] JLD2 v0.5.11
  [692b3bcd] JLLWrappers v1.7.0
  [682c06a0] JSON v0.21.4
  [9c8b4983] LightXML v0.9.1
  [d3d80556] LineSearches v7.3.0
⌅ [2ab3a3ac] LogExpFunctions v0.3.28
  [da04e1cc] MPI v0.20.22
  [3da0fdf6] MPIPreferences v0.1.11
  [1914dd2f] MacroTools v0.5.15
  [d41bc354] NLSolversBase v7.8.3
  [2774e3e8] NLsolve v4.5.1
⌅ [77ba4419] NaNMath v1.0.3
  [b8a86587] NearestNeighbors v0.4.21
  [6fe1bfb0] OffsetArrays v1.15.0
  [bac558e1] OrderedCollections v1.8.0
  [d96e819e] Parameters v0.12.3
  [69de0a69] Parsers v2.8.1
⌅ [5a9dfac6] PartitionedArrays v0.3.4
  [eebad327] PkgVersion v0.3.3
  [c74db56a] PolynomialBases v0.4.22
  [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.4.3
  [1fd47b50] QuadGK v2.11.2
  [3cdcf5f2] RecipesBase v1.3.4
  [189a3867] Reexport v1.2.2
  [ae029012] Requires v1.3.0
  [efcf1570] Setfield v1.1.1
  [ce78b400] SimpleUnPack v1.1.0
  [a0a7dd2c] SparseMatricesCSR v0.6.8
  [276daf66] SpecialFunctions v2.5.0
  [90137ffa] StaticArrays v1.9.12
  [1e83bf80] StaticArraysCore v1.4.3
  [82ae8749] StatsAPI v1.7.0
  [3bb67fe8] TranscodingStreams v0.11.3
  [3a884ed6] UnPack v1.0.2
  [4004b06d] VTKBase v1.0.1
  [64499a7a] WriteVTK v1.21.1
  [f5851436] FFTW_jll v3.3.10+3
  [e33a78d0] Hwloc_jll v2.11.2+3
  [1d5cc7b8] IntelOpenMP_jll v2025.0.4+0
  [94ce4f54] Libiconv_jll v1.18.0+0
  [856f044c] MKL_jll v2025.0.1+1
  [7cb0a576] MPICH_jll v4.2.3+0
  [f1f71cc9] MPItrampoline_jll v5.5.1+2
  [9237b28f] MicrosoftMPI_jll v10.1.4+3
⌅ [656ef2d0] OpenBLAS32_jll v0.3.21+0
  [fe0851c0] OpenMPI_jll v5.0.6+0
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
⌅ [8fa3689e] PETSc_jll v3.15.2+0
  [02c8fc9c] XML2_jll v2.13.6+0
  [1317d2d5] oneTBB_jll v2021.12.0+0
  [0dad84c5] ArgTools v1.1.1
  [56f22d72] Artifacts
  [2a0f44e3] Base64
  [ade2ca70] Dates
  [8ba89e20] Distributed
  [f43a241f] Downloads v1.6.0
  [7b1f6079] FileWatching
  [9fa8497b] Future
  [b77e0a4c] InteractiveUtils
  [4af54fe1] LazyArtifacts
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [56ddb016] Logging
  [d6f4376e] Markdown
  [a63ad114] Mmap
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.9.2
  [de0858da] Printf
  [3fa0cd96] REPL
  [9a3f8284] Random
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization
  [6462fe0b] Sockets
  [2f01184e] SparseArrays
  [10745b16] Statistics v1.9.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test
  [cf7118a7] UUIDs
  [4ec0a83e] Unicode
  [e66e0078] CompilerSupportLibraries_jll v1.0.5+0
  [deac9b47] LibCURL_jll v8.4.0+0
  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.2+0
  [14a3606d] MozillaCACerts_jll v2022.10.11
  [4536629a] OpenBLAS_jll v0.3.21+4
  [05823500] OpenLibm_jll v0.8.1+0
  [bea87d4a] SuiteSparse_jll v5.10.1+6
  [83775a58] Zlib_jll v1.2.13+0
  [8e850b90] libblastrampoline_jll v5.8.0+0
  [8e850ede] nghttp2_jll v1.52.0+1
  [3f19e933] p7zip_jll v17.4.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
Precompiling project...
  97 dependencies successfully precompiled in 42 seconds. 7 already precompiled.
     Testing Running tests...
[0] PetscDetermineInitialFPTrap(): Floating point trapping is off by default 0
[0] PetscInitialize(): PETSc successfully started: number of processors = 1
[0] PetscGetHostName(): Rejecting domainname, likely is NIS b3c7fea75999.(none)
[0] PetscInitialize(): Running on machine: b3c7fea75999
[0] PetscCommDuplicate(): Duplicating a communicator 1140850689 -2080374784 max tags = 268435455
[0] PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] PetscGetHostName(): Rejecting domainname, likely is NIS b3c7fea75999.(none)
Vec Object: 1 MPI processes
  type: seq
1.
2.
4.
1.
[0] PetscCommDuplicate(): Duplicating a communicator 1140850688 -2080374783 max tags = 268435455
[0] PetscGetHostName(): Rejecting domainname, likely is NIS b3c7fea75999.(none)
Vec Object: 1 MPI processes
  type: seq
1.
2.
4.
1.
Vec Object: 1 MPI processes
  type: seq
50.
60.
4.
1.
PETSC: Test Failed at /shared/test/sequential/PETSCTests.jl:44
  Expression: array[ids .+ 1] == vals2
   Evaluated: [50.0, 60.0, 1.0] == [50.0, 50.0, 60.0]

Stacktrace:
 [1] top-level scope
   @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:478
 [2] include(mod::Module, _path::String)
   @ Base ./Base.jl:457
 [3] include
   @ /shared/test/sequential/runtests.jl:1 [inlined]
 [4] macro expansion
   @ /shared/test/sequential/runtests.jl:6 [inlined]
 [5] macro expansion
   @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
 [6] macro expansion
   @ /shared/test/sequential/runtests.jl:6 [inlined]
 [7] top-level scope
   @ ./timing.jl:273 [inlined]
 [8] top-level scope
   @ /shared/test/sequential/runtests.jl:0
[0] PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 5; storage space: 13 unneeded,7 used
[0] MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
[0] MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 3
[0] MatCheckCompressedRow(): Found the ratio (num_zerorows 1)/(num_localrows 4) < 0.6. Do not use CompressedRow routines.
[0] MatSeqAIJCheckInode(): Found 4 nodes out of 4 rows. Not using Inode routines
PETSC: Test Failed at /shared/test/sequential/PETSCTests.jl:77
  Expression: v2 == PetscScalar[3.0, 2.0, 3.0, 4.0, 11.0, 6.0]
   Evaluated: [4.0, 12.0, 4.0, 12.0, 5.0, 6.0] == [3.0, 2.0, 3.0, 4.0, 11.0, 6.0]

Stacktrace:
 [1] top-level scope
   @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:478
 [2] include(mod::Module, _path::String)
   @ Base ./Base.jl:457
 [3] include
   @ /shared/test/sequential/runtests.jl:1 [inlined]
 [4] macro expansion
   @ /shared/test/sequential/runtests.jl:6 [inlined]
 [5] macro expansion
   @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
 [6] macro expansion
   @ /shared/test/sequential/runtests.jl:6 [inlined]
 [7] top-level scope
   @ ./timing.jl:273 [inlined]
 [8] top-level scope
   @ /shared/test/sequential/runtests.jl:0
Mat Object: 1 MPI processes
  type: seqaij
row 0: (0, 12.)  (3, 4.)  (4, 4.) 
row 1:
row 2: (0, 6.)  (3, 5.) 
row 3: (0, 6.)  (4, 5.) 
[0] PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 4; storage space: 0 unneeded,5 used
[0] MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
[0] MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 5
[0] MatCheckCompressedRow(): Found the ratio (num_zerorows 2)/(num_localrows 4) < 0.6. Do not use CompressedRow routines.
[0] MatSeqAIJCheckInode(): Found 4 nodes out of 4 rows. Not using Inode routines
Mat Object: 1 MPI processes
  type: seqaij
row 0:
row 1: (0, 4.)  (0, -2.) 
row 2:
row 3: (0, 4.)  (0, -2.)  (1, -1.)  (0, 6.)  (0, -2.) 
[0] PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] PCSetUp(): Setting up PC for first time
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp_Jacobi(): Zero detected in diagonal of matrix, using 1 at those locations
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] KSPGMRESCycle(): Residual norm computed by GMRES recursion formula 2.17806 is far from the computed residual norm 9.38293 at restart, residual norm at start of cycle 5.56776PETSC: Test Failed at /shared/test/sequential/PETSCTests.jl:133
  Expression: x ≈ x2
   Evaluated: [1.0, 1.0, 1.0, 1.0] ≈ [5.147941802412766, 32.557709571041855, 10.864940485150921, 1.682174525521201e16]

Stacktrace:
 [1] top-level scope
   @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:478
 [2] include(mod::Module, _path::String)
   @ Base ./Base.jl:457
 [3] include
   @ /shared/test/sequential/runtests.jl:1 [inlined]
 [4] macro expansion
   @ /shared/test/sequential/runtests.jl:6 [inlined]
 [5] macro expansion
   @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
 [6] macro expansion
   @ /shared/test/sequential/runtests.jl:6 [inlined]
 [7] top-level scope
   @ ./timing.jl:273 [inlined]
 [8] top-level scope
   @ /shared/test/sequential/runtests.jl:0
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] KSPGMRESCycle(): Residual norm computed by GMRES recursion formula 2.17806 is far from the computed residual norm 9.38293 at restart, residual norm at start of cycle 5.56776PETSC: Test Failed at /shared/test/sequential/PETSCTests.jl:138
  Expression: x ≈ x2
   Evaluated: [1.0, 1.0, 1.0, 1.0] ≈ [5.147941802412766, 32.557709571041855, 10.864940485150921, 1.682174525521201e16]

Stacktrace:
 [1] top-level scope
   @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:478
 [2] include(mod::Module, _path::String)
   @ Base ./Base.jl:457
 [3] include
   @ /shared/test/sequential/runtests.jl:1 [inlined]
 [4] macro expansion
   @ /shared/test/sequential/runtests.jl:6 [inlined]
 [5] macro expansion
   @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
 [6] macro expansion
   @ /shared/test/sequential/runtests.jl:6 [inlined]
 [7] top-level scope
   @ ./timing.jl:273 [inlined]
 [8] top-level scope
   @ /shared/test/sequential/runtests.jl:0
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] PCSetUp(): Leaving PC with identical preconditioner since operator is unchanged
[0] KSPGMRESCycle(): Residual norm computed by GMRES recursion formula 3.30006 is far from the computed residual norm 31.4115 at restart, residual norm at start of cycle 5.56776PETSC: Test Failed at /shared/test/sequential/PETSCTests.jl:142
  Expression: x ≈ x2
   Evaluated: [1.0, 1.0, 1.0, 1.0] ≈ [-1.305474746949631e17, 17.742541443206637, -19.300650140068257, -10.463860515124141]

Stacktrace:
 [1] top-level scope
   @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:478
 [2] include(mod::Module, _path::String)
   @ Base ./Base.jl:457
 [3] include
   @ /shared/test/sequential/runtests.jl:1 [inlined]
 [4] macro expansion
   @ /shared/test/sequential/runtests.jl:6 [inlined]
 [5] macro expansion
   @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
 [6] macro expansion
   @ /shared/test/sequential/runtests.jl:6 [inlined]
 [7] top-level scope
   @ ./timing.jl:273 [inlined]
 [8] top-level scope
   @ /shared/test/sequential/runtests.jl:0
KSP Object: (p_) 1 MPI processes
  type: gmres
    restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
    happy breakdown tolerance 1e-30
  maximum iterations=10000, initial guess is zero
  tolerances:  relative=1e-05, absolute=1e-50, divergence=10000.
  left preconditioning
  using PRECONDITIONED norm type for convergence test
PC Object: (p_) 1 MPI processes
  type: jacobi
    type DIAGONAL
  linear system matrix = precond matrix:
  Mat Object: 1 MPI processes
    type: seqaij
    rows=4, cols=4
    total: nonzeros=5, allocated nonzeros=0
    total number of mallocs used during MatSetValues calls=0
      not using I-node routines
[0] PetscFinalize(): PetscFinalize() called
[0] Petsc_DelViewer(): Removing viewer data attribute in an MPI_Comm -2080374784
[0] Petsc_OuterComm_Attr_Delete_Fn(): Removing reference to PETSc communicator embedded in a user MPI_Comm -2080374784
[0] Petsc_InnerComm_Attr_Delete_Fn(): User MPI_Comm 1140850689 is being unlinked from inner PETSc comm -2080374784
[0] PetscCommDestroy(): Deleting PETSc MPI_Comm -2080374784
[0] Petsc_Counter_Attr_Delete_Fn(): Deleting counter data in an MPI_Comm -2080374784
[0] Petsc_DelViewer(): Removing viewer data attribute in an MPI_Comm -2080374783
[0] Petsc_OuterComm_Attr_Delete_Fn(): Removing reference to PETSc communicator embedded in a user MPI_Comm -2080374783
[0] Petsc_InnerComm_Attr_Delete_Fn(): User MPI_Comm 1140850688 is being unlinked from inner PETSc comm -2080374783
[0] PetscCommDestroy(): Deleting PETSc MPI_Comm -2080374783
[0] Petsc_Counter_Attr_Delete_Fn(): Deleting counter data in an MPI_Comm -2080374783
  3.081598 seconds (9.95 M allocations: 791.745 MiB, 3.71% gc time, 27.64% compilation time: <1% of which was recompilation)
[0] PetscDetermineInitialFPTrap(): Floating point trapping is off by default 0
[0] PetscInitialize(): PETSc successfully started: number of processors = 1
[0] PetscGetHostName(): Rejecting domainname, likely is NIS b3c7fea75999.(none)
[0] PetscInitialize(): Running on machine: b3c7fea75999
[0] PetscCommDuplicate(): Duplicating a communicator 1140850689 -2080374783 max tags = 268435455
PETScArrays: Test Failed at /shared/test/sequential/PETScArraysTests.jl:17
  Expression: length(v) == n
   Evaluated: 281470681743370 == 10

Stacktrace:
 [1] macro expansion
   @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:478 [inlined]
 [2] (::Main.GridapPETScTests.GridapPETScSequentialTests.PETScArraysTests.var"#1#2")()
   @ Main.GridapPETScTests.GridapPETScSequentialTests.PETScArraysTests /shared/test/sequential/PETScArraysTests.jl:17
[0] PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374783
[0] PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374783
[0] PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374783
[0] PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374783
[0] PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374783
[0] MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 5; storage space: 20 unneeded,0 used
[0] MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
[0] MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 0
[0] MatCheckCompressedRow(): Found the ratio (num_zerorows 4)/(num_localrows 4) > 0.6. Use CompressedRow routines.
[0] MatSeqAIJCheckInode(): Found 1 nodes of 4. Limit used: 5. Using Inode routines
PETScArrays: Test Failed at /shared/test/sequential/PETScArraysTests.jl:43
  Expression: size(A) == (m, n)
   Evaluated: (281470681743364, 5) == (4, 5)

Stacktrace:
 [1] macro expansion
   @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:478 [inlined]
 [2] (::Main.GridapPETScTests.GridapPETScSequentialTests.PETScArraysTests.var"#1#2")()
   @ Main.GridapPETScTests.GridapPETScSequentialTests.PETScArraysTests /shared/test/sequential/PETScArraysTests.jl:43
[0] MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 5; storage space: 14 unneeded,1 used
[0] MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 1
[0] MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 1
[0] MatCheckCompressedRow(): Found the ratio (num_zerorows 3)/(num_localrows 4) > 0.6. Use CompressedRow routines.
[0] MatSeqAIJCheckInode(): Found 2 nodes of 4. Limit used: 5. Using Inode routines
[0] MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 5; storage space: 14 unneeded,2 used
[0] MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 1
[0] MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 1
[0] MatCheckCompressedRow(): Found the ratio (num_zerorows 2)/(num_localrows 4) < 0.6. Do not use CompressedRow routines.
[0] MatSeqAIJCheckInode(): Found 4 nodes out of 4 rows. Not using Inode routines
281470681743364×5 GridapPETSc.PETScMatrix:
[0] Petsc_OuterComm_Attr_Delete_Fn(): Removing reference to PETSc communicator embedded in a user MPI_Comm -2080374783
[0] Petsc_InnerComm_Attr_Delete_Fn(): User MPI_Comm 1140850689 is being unlinked from inner PETSc comm -2080374783
[0] PetscCommDestroy(): Deleting PETSc MPI_Comm -2080374783
[0] Petsc_Counter_Attr_Delete_Fn(): Deleting counter data in an MPI_Comm -2080374783
PETScArrays: Error During Test at /shared/test/sequential/runtests.jl:8
  Got exception outside of a @test
  LoadError: OutOfMemoryError()
  Stacktrace:
    [1] Array
      @ ./boot.jl:477 [inlined]
    [2] vcat
      @ ./range.jl:1357 [inlined]
    [3] _print_matrix(io::IOContext{Base.TTY}, X::AbstractVecOrMat, pre::String, sep::String, post::String, hdots::String, vdots::String, ddots::String, hmod::Int64, vmod::Int64, rowsA::UnitRange{Int64}, colsA::UnitRange{Int64})
      @ Base ./arrayshow.jl:197
    [4] print_matrix(io::IOContext{Base.TTY}, X::GridapPETSc.PETScMatrix, pre::String, sep::String, post::String, hdots::String, vdots::String, ddots::String, hmod::Int64, vmod::Int64)
      @ Base ./arrayshow.jl:171
    [5] print_matrix
      @ ./arrayshow.jl:171 [inlined]
    [6] print_array
      @ ./arrayshow.jl:358 [inlined]
    [7] show(io::Base.TTY, #unused#::MIME{Symbol("text/plain")}, X::GridapPETSc.PETScMatrix)
      @ Base ./arrayshow.jl:399
    [8] display(d::TextDisplay, M::MIME{Symbol("text/plain")}, x::Any)
      @ Base.Multimedia ./multimedia.jl:254
    [9] display
      @ ./multimedia.jl:255 [inlined]
   [10] display(x::Any)
      @ Base.Multimedia ./multimedia.jl:340
   [11] (::Main.GridapPETScTests.GridapPETScSequentialTests.PETScArraysTests.var"#1#2")()
      @ Main.GridapPETScTests.GridapPETScSequentialTests.PETScArraysTests /shared/test/sequential/PETScArraysTests.jl:48
   [12] with(f::Main.GridapPETScTests.GridapPETScSequentialTests.PETScArraysTests.var"#1#2"; kwargs::Base.Pairs{Symbol, Vector{SubString{String}}, Tuple{Symbol}, NamedTuple{(:args,), Tuple{Vector{SubString{String}}}}})
      @ GridapPETSc /shared/src/Environment.jl:38
   [13] top-level scope
      @ /shared/test/sequential/PETScArraysTests.jl:12
   [14] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [15] include
      @ /shared/test/sequential/runtests.jl:1 [inlined]
   [16] macro expansion
      @ /shared/test/sequential/runtests.jl:8 [inlined]
   [17] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [18] macro expansion
      @ /shared/test/sequential/runtests.jl:8 [inlined]
   [19] top-level scope
      @ ./timing.jl:273 [inlined]
   [20] top-level scope
      @ /shared/test/sequential/runtests.jl:0
   [21] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [22] include
      @ /shared/test/runtests.jl:1 [inlined]
   [23] macro expansion
      @ /shared/test/runtests.jl:5 [inlined]
   [24] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [25] macro expansion
      @ /shared/test/runtests.jl:5 [inlined]
   [26] top-level scope
      @ ./timing.jl:273 [inlined]
   [27] top-level scope
      @ /shared/test/runtests.jl:0
   [28] include(fname::String)
      @ Base.MainInclude ./client.jl:478
   [29] top-level scope
      @ none:6
   [30] eval
      @ ./boot.jl:370 [inlined]
   [31] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:280
   [32] _start()
      @ Base ./client.jl:522
  in expression starting at /shared/test/sequential/PETScArraysTests.jl:1
  1.008101 seconds (1.96 M allocations: 2.000 PiB, 2.28% gc time, 88.31% compilation time)
[0] PetscFinalize(): PetscFinalize() called
[1, 2, 3, 5, 6]
[4, 5, 7, 3, 6]
[6, 7, 4]
Vec Object: 1 MPI processes
  type: seq
10.
20.
30.
40.
50.
60.
70.
PartitionedArrays (sequential): Error During Test at /shared/test/sequential/runtests.jl:10
  Got exception outside of a @test
  LoadError: AssertionError: length(v) == length(ids)
  Stacktrace:
    [1] PartitionedArrays.PVector(v::GridapPETSc.PETScVector, ids::PartitionedArrays.PRange{PartitionedArrays.DebugArray{PartitionedArrays.OwnAndGhostIndices{Nothing}, 1}}, #unused#::PartitionedArrays.DebugArray{PartitionedArrays.OwnAndGhostIndices{Nothing}, 1})
      @ GridapPETSc /shared/src/PartitionedArrays.jl:58
    [2] PVector
      @ /shared/src/PartitionedArrays.jl:54 [inlined]
    [3] (::Main.GridapPETScTests.GridapPETScSequentialTests.PartitionedArraysTests.var"#test_vectors#15")(v::PartitionedArrays.PVector{Vector{Float64}, PartitionedArrays.DebugArray{Vector{Float64}, 1}, PartitionedArrays.DebugArray{PartitionedArrays.OwnAndGhostIndices{Nothing}, 1}, PartitionedArrays.DebugArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}, x::GridapPETSc.PETScVector, ids::PartitionedArrays.PRange{PartitionedArrays.DebugArray{PartitionedArrays.OwnAndGhostIndices{Nothing}, 1}})
      @ Main.GridapPETScTests.GridapPETScSequentialTests.PartitionedArraysTests /shared/test/PartitionedArraysTests.jl:108
    [4] partitioned_tests(distribute::Type{PartitionedArrays.DebugArray}, nparts::Int64)
      @ Main.GridapPETScTests.GridapPETScSequentialTests.PartitionedArraysTests /shared/test/PartitionedArraysTests.jl:125
    [5] (::Main.GridapPETScTests.GridapPETScSequentialTests.PartitionedArraysTests.var"#20#21")(distribute::Type)
      @ Main.GridapPETScTests.GridapPETScSequentialTests.PartitionedArraysTests /shared/test/sequential/PartitionedArraysTests.jl:5
    [6] with_debug(f::Main.GridapPETScTests.GridapPETScSequentialTests.PartitionedArraysTests.var"#20#21")
      @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/debug_array.jl:8
    [7] top-level scope
      @ /shared/test/sequential/PartitionedArraysTests.jl:4
    [8] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
    [9] include
      @ /shared/test/sequential/runtests.jl:1 [inlined]
   [10] macro expansion
      @ /shared/test/sequential/runtests.jl:10 [inlined]
   [11] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [12] macro expansion
      @ /shared/test/sequential/runtests.jl:10 [inlined]
   [13] top-level scope
      @ ./timing.jl:273 [inlined]
   [14] top-level scope
      @ /shared/test/sequential/runtests.jl:0
   [15] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [16] include
      @ /shared/test/runtests.jl:1 [inlined]
   [17] macro expansion
      @ /shared/test/runtests.jl:5 [inlined]
   [18] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [19] macro expansion
      @ /shared/test/runtests.jl:5 [inlined]
   [20] top-level scope
      @ ./timing.jl:273 [inlined]
   [21] top-level scope
      @ /shared/test/runtests.jl:0
   [22] include(fname::String)
      @ Base.MainInclude ./client.jl:478
   [23] top-level scope
      @ none:6
   [24] eval
      @ ./boot.jl:370 [inlined]
   [25] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:280
   [26] _start()
      @ Base ./client.jl:522
  in expression starting at /shared/test/sequential/PartitionedArraysTests.jl:1
  6.349533 seconds (25.72 M allocations: 1.342 GiB, 34.41% gc time, 91.18% compilation time)
[0]PETSC ERROR: --------------------- Error Message --------------------------------------------------------------
[0]PETSC ERROR: Object is in wrong state
[0]PETSC ERROR: Matrix is missing diagonal entry 0
[0]PETSC ERROR: See https://www.mcs.anl.gov/petsc/documentation/faq.html for trouble shooting.
[0]PETSC ERROR: Petsc Release Version 3.15.2, Jul 10, 2021 
[0]PETSC ERROR: GridapPETSc on a  named b3c7fea75999 by Unknown Tue Feb 11 16:50:21 2025
[0]PETSC ERROR: Configure options --prefix=/workspace/destdir CC=cc FC=gfortran CXX=c++ COPTFLAGS=-O3 CXXOPTFLAGS=-O3 CFLAGS=-fno-stack-protector FOPTFLAGS=-O3 --with-64-bit-indices=0 --with-debugging=0 --with-batch --PETSC_ARCH=aarch64-linux-gnu_double_real_Int32 --with-blaslapack-lib=/workspace/destdir/lib/libopenblas.so --with-blaslapack-suffix= --known-64-bit-blas-indices=0 --with-mpi-lib="[/workspace/destdir/lib/libmpifort.so,/workspace/destdir/lib/libmpi.so]" --known-mpi-int64_t=0 --with-mpi-include=/workspace/destdir/include --with-sowing=0 --with-precision=double --with-scalar-type=real
[0]PETSC ERROR: #1 MatILUFactorSymbolic_SeqAIJ() at /workspace/srcdir/petsc-3.15.2/src/mat/impls/aij/seq/aijfact.c:1686
[0]PETSC ERROR: #2 MatILUFactorSymbolic() at /workspace/srcdir/petsc-3.15.2/src/mat/interface/matrix.c:6921
[0]PETSC ERROR: #3 PCSetUp_ILU() at /workspace/srcdir/petsc-3.15.2/src/ksp/pc/impls/factor/ilu/ilu.c:141
[0]PETSC ERROR: #4 PCSetUp() at /workspace/srcdir/petsc-3.15.2/src/ksp/pc/interface/precon.c:1015
[0]PETSC ERROR: #5 KSPSetUp() at /workspace/srcdir/petsc-3.15.2/src/ksp/ksp/interface/itfunc.c:406
PETScLinearSolvers: Error During Test at /shared/test/sequential/runtests.jl:12
  Got exception outside of a @test
  LoadError: Petsc returned with error code: 73 
  Stacktrace:
    [1] macro expansion
      @ /shared/src/Config.jl:88 [inlined]
    [2] numerical_setup(ss::GridapPETSc.PETScLinearSolverSS{typeof(GridapPETSc.ksp_from_options)}, A::SparseMatricesCSR.SparseMatrixCSR{0, Float64, Int64})
      @ GridapPETSc /shared/src/PETScLinearSolvers.jl:58
    [3] solve(ls::GridapPETSc.PETScLinearSolver{typeof(GridapPETSc.ksp_from_options)}, A::SparseMatricesCSR.SparseMatrixCSR{0, Float64, Int64}, b::Vector{Float64})
      @ Gridap.Algebra ~/.julia/packages/Gridap/Ce4E8/src/Algebra/LinearSolvers.jl:79
    [4] top-level scope
      @ /shared/test/sequential/PETScLinearSolversTests.jl:27
    [5] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
    [6] include
      @ /shared/test/sequential/runtests.jl:1 [inlined]
    [7] macro expansion
      @ /shared/test/sequential/runtests.jl:12 [inlined]
    [8] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
    [9] macro expansion
      @ /shared/test/sequential/runtests.jl:12 [inlined]
   [10] top-level scope
      @ ./timing.jl:273 [inlined]
   [11] top-level scope
      @ /shared/test/sequential/runtests.jl:0
   [12] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [13] include
      @ /shared/test/runtests.jl:1 [inlined]
   [14] macro expansion
      @ /shared/test/runtests.jl:5 [inlined]
   [15] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [16] macro expansion
      @ /shared/test/runtests.jl:5 [inlined]
   [17] top-level scope
      @ ./timing.jl:273 [inlined]
   [18] top-level scope
      @ /shared/test/runtests.jl:0
   [19] include(fname::String)
      @ Base.MainInclude ./client.jl:478
   [20] top-level scope
      @ none:6
   [21] eval
      @ ./boot.jl:370 [inlined]
   [22] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:280
   [23] _start()
      @ Base ./client.jl:522
  in expression starting at /shared/test/sequential/PETScLinearSolversTests.jl:1
  0.166513 seconds (50.81 k allocations: 3.326 MiB, 40.09% gc time, 20.11% compilation time)
  0 SNES Function norm 4.242640687119e+00 
[0]PETSC ERROR: #6 MatSetValues_SeqAIJ() at /workspace/srcdir/petsc-3.15.2/src/mat/impls/aij/seq/aij.c:507
[0]PETSC ERROR: #7 MatSetValues() at /workspace/srcdir/petsc-3.15.2/src/mat/interface/matrix.c:1401
[0]PETSC ERROR: #8 MatCholeskyFactorSymbolic_SeqAIJ() at /workspace/srcdir/petsc-3.15.2/src/mat/impls/aij/seq/aijfact.c:2782
[0]PETSC ERROR: #9 MatCholeskyFactorSymbolic() at /workspace/srcdir/petsc-3.15.2/src/mat/interface/matrix.c:3314
[0]PETSC ERROR: #10 PCSetUp_Cholesky() at /workspace/srcdir/petsc-3.15.2/src/ksp/pc/impls/factor/cholesky/cholesky.c:83
[0]PETSC ERROR: #11 PCSetUp() at /workspace/srcdir/petsc-3.15.2/src/ksp/pc/interface/precon.c:1015
[0]PETSC ERROR: #12 KSPSetUp() at /workspace/srcdir/petsc-3.15.2/src/ksp/ksp/interface/itfunc.c:406
[0]PETSC ERROR: #13 KSPSolve_Private() at /workspace/srcdir/petsc-3.15.2/src/ksp/ksp/interface/itfunc.c:850
[0]PETSC ERROR: #14 KSPSolve() at /workspace/srcdir/petsc-3.15.2/src/ksp/ksp/interface/itfunc.c:1085
[0]PETSC ERROR: #15 SNESSolve_NEWTONLS() at /workspace/srcdir/petsc-3.15.2/src/snes/impls/ls/ls.c:225
[0]PETSC ERROR: #16 SNESSolve() at /workspace/srcdir/petsc-3.15.2/src/snes/interface/snes.c:4653
PETScNonLinearSolvers: Error During Test at /shared/test/sequential/runtests.jl:14
  Got exception outside of a @test
  LoadError: Petsc returned with error code: 73 
  Stacktrace:
    [1] macro expansion
      @ /shared/src/Config.jl:88 [inlined]
    [2] solve!(x::Vector{Float64}, nls::GridapPETSc.PETScNonlinearSolver{typeof(GridapPETSc.snes_from_options)}, op::Gridap.Algebra.NonlinearOperatorMock, #unused#::Nothing)
      @ GridapPETSc /shared/src/PETScNonlinearSolvers.jl:185
    [3] solve!
      @ ~/.julia/packages/Gridap/Ce4E8/src/Algebra/NonlinearSolvers.jl:22 [inlined]
    [4] test_nonlinear_solver(nls::GridapPETSc.PETScNonlinearSolver{typeof(GridapPETSc.snes_from_options)}, op::Gridap.Algebra.NonlinearOperatorMock, x0::Vector{Float64}, x::Vector{Float64}, pred::typeof(isapprox))
      @ Gridap.Algebra ~/.julia/packages/Gridap/Ce4E8/src/Algebra/NonlinearSolvers.jl:62
    [5] test_nonlinear_solver(nls::GridapPETSc.PETScNonlinearSolver{typeof(GridapPETSc.snes_from_options)}, op::Gridap.Algebra.NonlinearOperatorMock, x0::Vector{Float64}, x::Vector{Float64})
      @ Gridap.Algebra ~/.julia/packages/Gridap/Ce4E8/src/Algebra/NonlinearSolvers.jl:61
    [6] top-level scope
      @ /shared/test/sequential/PETScNonlinearSolversTests.jl:15
    [7] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
    [8] include
      @ /shared/test/sequential/runtests.jl:1 [inlined]
    [9] macro expansion
      @ /shared/test/sequential/runtests.jl:14 [inlined]
   [10] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [11] macro expansion
      @ /shared/test/sequential/runtests.jl:14 [inlined]
   [12] top-level scope
      @ ./timing.jl:273 [inlined]
   [13] top-level scope
      @ /shared/test/sequential/runtests.jl:0
   [14] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [15] include
      @ /shared/test/runtests.jl:1 [inlined]
   [16] macro expansion
      @ /shared/test/runtests.jl:5 [inlined]
   [17] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [18] macro expansion
      @ /shared/test/runtests.jl:5 [inlined]
   [19] top-level scope
      @ ./timing.jl:273 [inlined]
   [20] top-level scope
      @ /shared/test/runtests.jl:0
   [21] include(fname::String)
      @ Base.MainInclude ./client.jl:478
   [22] top-level scope
      @ none:6
   [23] eval
      @ ./boot.jl:370 [inlined]
   [24] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:280
   [25] _start()
      @ Base ./client.jl:522
  in expression starting at /shared/test/sequential/PETScNonlinearSolversTests.jl:1
  0.320604 seconds (628.78 k allocations: 43.239 MiB, 20.45% gc time, 59.72% compilation time)
[0] PetscDetermineInitialFPTrap(): Floating point trapping is off by default 0
[0] PetscInitialize(): PETSc successfully started: number of processors = 1
[0] PetscGetHostName(): Rejecting domainname, likely is NIS b3c7fea75999.(none)
[0] PetscInitialize(): Running on machine: b3c7fea75999
[0] PetscCommDuplicate(): Duplicating a communicator 1140850689 -2080374783 max tags = 268435455
[0] MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 3; storage space: 3 unneeded,0 used
[0] MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
[0] MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 0
[0] MatCheckCompressedRow(): Found the ratio (num_zerorows 4)/(num_localrows 4) > 0.6. Use CompressedRow routines.
[0] MatSeqAIJCheckInode(): Found 1 nodes of 4. Limit used: 5. Using Inode routines
281470681743364×281470681743363 GridapPETSc.PETScMatrix:
[0] Petsc_OuterComm_Attr_Delete_Fn(): Removing reference to PETSc communicator embedded in a user MPI_Comm -2080374783
[0] Petsc_InnerComm_Attr_Delete_Fn(): User MPI_Comm 1140850689 is being unlinked from inner PETSc comm -2080374783
[0] PetscCommDestroy(): Deleting PETSc MPI_Comm -2080374783
[0] Petsc_Counter_Attr_Delete_Fn(): Deleting counter data in an MPI_Comm -2080374783
PETScAssembly: Error During Test at /shared/test/sequential/runtests.jl:16
  Got exception outside of a @test
  LoadError: OutOfMemoryError()
  Stacktrace:
    [1] Array
      @ ./boot.jl:477 [inlined]
    [2] vcat
      @ ./range.jl:1357 [inlined]
    [3] _print_matrix(io::IOContext{Base.TTY}, X::AbstractVecOrMat, pre::String, sep::String, post::String, hdots::String, vdots::String, ddots::String, hmod::Int64, vmod::Int64, rowsA::UnitRange{Int64}, colsA::UnitRange{Int64})
      @ Base ./arrayshow.jl:197
    [4] print_matrix(io::IOContext{Base.TTY}, X::GridapPETSc.PETScMatrix, pre::String, sep::String, post::String, hdots::String, vdots::String, ddots::String, hmod::Int64, vmod::Int64)
      @ Base ./arrayshow.jl:171
    [5] print_matrix
      @ ./arrayshow.jl:171 [inlined]
    [6] print_array
      @ ./arrayshow.jl:358 [inlined]
    [7] show(io::Base.TTY, #unused#::MIME{Symbol("text/plain")}, X::GridapPETSc.PETScMatrix)
      @ Base ./arrayshow.jl:399
    [8] display(d::TextDisplay, M::MIME{Symbol("text/plain")}, x::Any)
      @ Base.Multimedia ./multimedia.jl:254
    [9] display
      @ ./multimedia.jl:255 [inlined]
   [10] display(x::Any)
      @ Base.Multimedia ./multimedia.jl:340
   [11] (::Main.GridapPETScTests.GridapPETScSequentialTests.PETScAssemblyTests.var"#1#2")()
      @ Main.GridapPETScTests.GridapPETScSequentialTests.PETScAssemblyTests /shared/test/sequential/PETScAssemblyTests.jl:39
   [12] with(f::Main.GridapPETScTests.GridapPETScSequentialTests.PETScAssemblyTests.var"#1#2"; kwargs::Base.Pairs{Symbol, Vector{SubString{String}}, Tuple{Symbol}, NamedTuple{(:args,), Tuple{Vector{SubString{String}}}}})
      @ GridapPETSc /shared/src/Environment.jl:38
   [13] top-level scope
      @ /shared/test/sequential/PETScAssemblyTests.jl:14
   [14] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [15] include
      @ /shared/test/sequential/runtests.jl:1 [inlined]
   [16] macro expansion
      @ /shared/test/sequential/runtests.jl:16 [inlined]
   [17] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [18] macro expansion
      @ /shared/test/sequential/runtests.jl:16 [inlined]
   [19] top-level scope
      @ ./timing.jl:273 [inlined]
   [20] top-level scope
      @ /shared/test/sequential/runtests.jl:0
   [21] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [22] include
      @ /shared/test/runtests.jl:1 [inlined]
   [23] macro expansion
      @ /shared/test/runtests.jl:5 [inlined]
   [24] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [25] macro expansion
      @ /shared/test/runtests.jl:5 [inlined]
   [26] top-level scope
      @ ./timing.jl:273 [inlined]
   [27] top-level scope
      @ /shared/test/runtests.jl:0
   [28] include(fname::String)
      @ Base.MainInclude ./client.jl:478
   [29] top-level scope
      @ none:6
   [30] eval
      @ ./boot.jl:370 [inlined]
   [31] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:280
   [32] _start()
      @ Base ./client.jl:522
  in expression starting at /shared/test/sequential/PETScAssemblyTests.jl:1
  0.663806 seconds (797.07 k allocations: 2.000 PiB, 29.41% gc time, 68.09% compilation time)
[0] PetscFinalize(): PetscFinalize() called
ERROR: Package GridapPETSc errored during testing (received signal: 11)

What am I doing wrong?

[JordiManyer]

Technically resolved by #109 , but from my testing MUMPS doesn't really work in parallel due to a lack of PSCOTCH or PARMETIS being bundled into the artifact.

[lamBOOO]

I can confirm that the serial tests now work on Apple M4 with the setup of #102 (comment) and the current main.

The 3 test that use mpiexec -n ... also don't run.

Log:

Details

(GridapPETSc) pkg> build
    Building GridapPETSc → `/shared/deps/build.log`
Precompiling project...
  2 dependencies successfully precompiled in 1 seconds. 104 already precompiled. 1 skipped during auto due to previous errors.

(GridapPETSc) pkg> instantiate

julia> using GridapPETSc
[ Info: Precompiling GridapPETSc [bcdc36c2-0c3e-11ea-095a-c9dadae499f1]

(GridapPETSc) pkg> test
     Testing GridapPETSc
      Status `/tmp/jl_5PGInh/Project.toml`
  [56d4f2e9] Gridap v0.19.1
  [f9701e48] GridapDistributed v0.4.8
  [bcdc36c2] GridapPETSc v0.5.4 `/shared`
  [da04e1cc] MPI v0.20.22
⌅ [5a9dfac6] PartitionedArrays v0.3.4
  [a0a7dd2c] SparseMatricesCSR v0.6.9
  [8fa3689e] PETSc_jll v3.22.0+0
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [9a3f8284] Random
  [2f01184e] SparseArrays
  [8dfed614] Test
      Status `/tmp/jl_5PGInh/Manifest.toml`
  [621f4979] AbstractFFTs v1.5.0
  [1520ce14] AbstractTrees v0.4.5
  [79e6a3ab] Adapt v4.3.0
⌅ [dce04be8] ArgCheck v2.4.0
⌅ [4fba245c] ArrayInterface v7.7.1
⌅ [4c555306] ArrayLayouts v1.10.4
  [15f4f7f2] AutoHashEquals v2.2.0
  [fbb218c0] BSON v0.3.9
⌅ [8e7c35d0] BlockArrays v1.2.0
  [7a955b69] CircularArrays v1.4.0
  [944b1d66] CodecZlib v0.7.8
  [861a8166] Combinatorics v1.0.3
  [bbf7d656] CommonSubexpressions v0.3.1
  [34da2185] Compat v4.16.0
⌅ [187b0558] ConstructionBase v1.5.8
  [864edb3b] DataStructures v0.18.22
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [b4f34e82] Distances v0.10.12
  [ffbed154] DocStringExtensions v0.9.5
  [7a1cc6ca] FFTW v1.9.0
  [442a2c76] FastGaussQuadrature v1.0.2
  [5789e2e9] FileIO v1.17.0
  [1a297f60] FillArrays v1.13.0
⌅ [6a86dc24] FiniteDiff v2.22.0
⌅ [f6369f11] ForwardDiff v0.10.38
  [56d4f2e9] Gridap v0.19.1
  [f9701e48] GridapDistributed v0.4.8
  [bcdc36c2] GridapPETSc v0.5.4 `/shared`
  [92d709cd] IrrationalConstants v0.2.4
  [42fd0dbc] IterativeSolvers v0.9.4
  [033835bb] JLD2 v0.5.13
  [692b3bcd] JLLWrappers v1.7.0
  [682c06a0] JSON v0.21.4
  [9c8b4983] LightXML v0.9.1
  [d3d80556] LineSearches v7.4.0
⌅ [2ab3a3ac] LogExpFunctions v0.3.28
  [da04e1cc] MPI v0.20.22
  [3da0fdf6] MPIPreferences v0.1.11
  [1914dd2f] MacroTools v0.5.16
⌅ [d41bc354] NLSolversBase v7.8.3
  [2774e3e8] NLsolve v4.5.1
⌅ [77ba4419] NaNMath v1.0.3
  [b8a86587] NearestNeighbors v0.4.21
  [6fe1bfb0] OffsetArrays v1.17.0
  [bac558e1] OrderedCollections v1.8.1
  [d96e819e] Parameters v0.12.3
  [69de0a69] Parsers v2.8.3
⌅ [5a9dfac6] PartitionedArrays v0.3.4
  [eebad327] PkgVersion v0.3.3
  [c74db56a] PolynomialBases v0.4.22
⌅ [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.4.3
  [1fd47b50] QuadGK v2.11.2
  [3cdcf5f2] RecipesBase v1.3.4
  [189a3867] Reexport v1.2.2
  [ae029012] Requires v1.3.1
  [efcf1570] Setfield v1.1.2
  [ce78b400] SimpleUnPack v1.1.0
  [a0a7dd2c] SparseMatricesCSR v0.6.9
  [276daf66] SpecialFunctions v2.5.1
  [90137ffa] StaticArrays v1.9.13
  [1e83bf80] StaticArraysCore v1.4.3
  [82ae8749] StatsAPI v1.7.1
  [3bb67fe8] TranscodingStreams v0.11.3
  [3a884ed6] UnPack v1.0.2
  [4004b06d] VTKBase v1.0.1
  [64499a7a] WriteVTK v1.21.2
  [f5851436] FFTW_jll v3.3.11+0
  [e33a78d0] Hwloc_jll v2.12.1+0
  [1d5cc7b8] IntelOpenMP_jll v2025.0.4+0
  [94ce4f54] Libiconv_jll v1.18.0+0
  [856f044c] MKL_jll v2025.0.1+1
  [7cb0a576] MPICH_jll v4.3.0+1
  [f1f71cc9] MPItrampoline_jll v5.5.3+0
  [9237b28f] MicrosoftMPI_jll v10.1.4+3
⌅ [656ef2d0] OpenBLAS32_jll v0.3.21+0
  [fe0851c0] OpenMPI_jll v5.0.8+0
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
  [8fa3689e] PETSc_jll v3.22.0+0
  [aabda75e] SCALAPACK32_jll v2.2.1+1
⌅ [02c8fc9c] XML2_jll v2.13.6+1
  [1317d2d5] oneTBB_jll v2022.0.0+0
  [0dad84c5] ArgTools v1.1.1
  [56f22d72] Artifacts
  [2a0f44e3] Base64
  [ade2ca70] Dates
  [8ba89e20] Distributed
  [f43a241f] Downloads v1.6.0
  [7b1f6079] FileWatching
  [9fa8497b] Future
  [b77e0a4c] InteractiveUtils
  [4af54fe1] LazyArtifacts
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [56ddb016] Logging
  [d6f4376e] Markdown
  [a63ad114] Mmap
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.9.2
  [de0858da] Printf
  [3fa0cd96] REPL
  [9a3f8284] Random
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization
  [6462fe0b] Sockets
  [2f01184e] SparseArrays
  [10745b16] Statistics v1.9.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test
  [cf7118a7] UUIDs
  [4ec0a83e] Unicode
  [e66e0078] CompilerSupportLibraries_jll v1.0.5+0
  [deac9b47] LibCURL_jll v8.4.0+0
  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.2+0
  [14a3606d] MozillaCACerts_jll v2022.10.11
  [4536629a] OpenBLAS_jll v0.3.21+4
  [05823500] OpenLibm_jll v0.8.1+0
  [bea87d4a] SuiteSparse_jll v5.10.1+6
  [83775a58] Zlib_jll v1.2.13+0
  [8e850b90] libblastrampoline_jll v5.8.0+0
  [8e850ede] nghttp2_jll v1.52.0+1
  [3f19e933] p7zip_jll v17.4.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
Precompiling project...
  100 dependencies successfully precompiled in 41 seconds. 7 already precompiled.
     Testing Running tests...
[0] <sys> PetscDetermineInitialFPTrap(): Floating point trapping is off by default 0
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDeviceType host available, initializing
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDevice host initialized, default device id 0, view FALSE, init type lazy
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDeviceType cuda not available
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDeviceType hip not available
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDeviceType sycl not available
[0] <sys> PetscInitialize_Common(): PETSc successfully started: number of processors = 1
[0] <sys> PetscGetHostName(): Rejecting domainname, likely is NIS cdb4b9906329.(none)
[0] <sys> PetscInitialize_Common(): Running on machine: cdb4b9906329
[0] <sys> PetscCommDuplicate(): Duplicating a communicator 1140850689 -2080374784 max tags = 1073741823
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscGetHostName(): Rejecting domainname, likely is NIS cdb4b9906329.(none)
Vec Object: 1 MPI process
  type: seq
1.
2.
4.
1.
[0] <sys> PetscCommDuplicate(): Duplicating a communicator 1140850688 -2080374783 max tags = 1073741823
[0] <sys> PetscGetHostName(): Rejecting domainname, likely is NIS cdb4b9906329.(none)
Vec Object: 1 MPI process
  type: seq
1.
2.
4.
1.
Vec Object: 1 MPI process
  type: seq
20.
40.
4.
60.
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 5; storage space: 10 unneeded,10 used
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 3
[0] <mat:seqaij> MatCheckCompressedRow(): Found the ratio (num_zerorows 0)/(num_localrows 4) < 0.6. Do not use CompressedRow routines.
[0] <mat:seqaij> MatSeqAIJCheckInode(): Found 3 nodes of 4. Limit used: 5. Using Inode routines
Mat Object: 1 MPI process
  type: seqaij
row 0: (1, 2.)  (3, 3.)  (4, 1.) 
row 1: (1, 6.)  (3, 11.)  (4, 5.) 
row 2: (1, 4.)  (3, 3.) 
row 3: (3, 4.)  (4, 3.) 
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 4; storage space: 0 unneeded,10 used
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 3
[0] <mat:seqaij> MatCheckCompressedRow(): Found the ratio (num_zerorows 0)/(num_localrows 4) < 0.6. Do not use CompressedRow routines.
[0] <mat:seqaij> MatSeqAIJCheckInode(): Found 4 nodes out of 4 rows. Not using Inode routines
Mat Object: 1 MPI process
  type: seqaij
row 0: (0, 4.)  (1, -2.) 
row 1: (0, -1.)  (1, 6.)  (2, -2.) 
row 2: (1, -1.)  (2, 6.)  (3, -2.) 
row 3: (2, -1.)  (3, 4.) 
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <ksp:gmres> KSPConvergedDefault(): Linear solver has converged. Residual norm 7.848199861801e-17 is less than relative tolerance 1.000000000000e-05 times initial right-hand side norm 1.145643923739e+00 at iteration 4
[0] <ksp:gmres> KSPConvergedDefault(): Linear solver has converged. Residual norm 7.848199861801e-17 is less than relative tolerance 1.000000000000e-05 times initial right-hand side norm 1.145643923739e+00 at iteration 4
[0] <ksp:gmres> KSPConvergedDefault(): Linear solver has converged. Residual norm 1.301969085041e-16 is less than relative tolerance 1.000000000000e-05 times initial right-hand side norm 1.145643923739e+00 at iteration 4
KSP Object: (p_) 1 MPI process
  type: gmres
    restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
    happy breakdown tolerance 1e-30
  maximum iterations=10000, initial guess is zero
  tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
  left preconditioning
  using PRECONDITIONED norm type for convergence test
PC Object: (p_) 1 MPI process
  type: jacobi
    type DIAGONAL
  linear system matrix = precond matrix:
  Mat Object: 1 MPI process
    type: seqaij
    rows=4, cols=4
    total: nonzeros=10, allocated nonzeros=0
    total number of mallocs used during MatSetValues calls=0
      not using I-node routines
[0] <sys> PetscFinalize(): PetscFinalize() called
[0] <sys> Petsc_OuterComm_Attr_DeleteFn(): Removing reference to PETSc communicator embedded in a user MPI_Comm -2080374783
[0] <sys> Petsc_InnerComm_Attr_DeleteFn(): User MPI_Comm 1140850688 is being unlinked from inner PETSc comm -2080374783
[0] <sys> PetscCommDestroy(): Deleting PETSc MPI_Comm -2080374783
[0] <sys> Petsc_Counter_Attr_DeleteFn(): Deleting counter data in an MPI_Comm -2080374783
[0] <sys> Petsc_OuterComm_Attr_DeleteFn(): Removing reference to PETSc communicator embedded in a user MPI_Comm -2080374784
[0] <sys> Petsc_InnerComm_Attr_DeleteFn(): User MPI_Comm 1140850689 is being unlinked from inner PETSc comm -2080374784
[0] <sys> PetscCommDestroy(): Deleting PETSc MPI_Comm -2080374784
[0] <sys> Petsc_Counter_Attr_DeleteFn(): Deleting counter data in an MPI_Comm -2080374784
  2.546674 seconds (9.28 M allocations: 747.620 MiB, 4.49% gc time, 24.13% compilation time: 1% of which was recompilation)
[0] <sys> PetscDetermineInitialFPTrap(): Floating point trapping is off by default 0
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDeviceType host available, initializing
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDevice host initialized, default device id 0, view FALSE, init type lazy
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDeviceType cuda not available
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDeviceType hip not available
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDeviceType sycl not available
[0] <sys> PetscInitialize_Common(): PETSc successfully started: number of processors = 1
[0] <sys> PetscGetHostName(): Rejecting domainname, likely is NIS cdb4b9906329.(none)
[0] <sys> PetscInitialize_Common(): Running on machine: cdb4b9906329
[0] <sys> PetscCommDuplicate(): Duplicating a communicator 1140850689 -2080374784 max tags = 1073741823
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 5; storage space: 20 unneeded,0 used
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 0
[0] <mat:seqaij> MatCheckCompressedRow(): Found the ratio (num_zerorows 4)/(num_localrows 4) > 0.6. Use CompressedRow routines.
[0] <mat:seqaij> MatSeqAIJCheckInode(): Found 1 nodes of 4. Limit used: 5. Using Inode routines
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 5; storage space: 14 unneeded,1 used
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 1
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 1
[0] <mat:seqaij> MatCheckCompressedRow(): Found the ratio (num_zerorows 3)/(num_localrows 4) > 0.6. Use CompressedRow routines.
[0] <mat:seqaij> MatSeqAIJCheckInode(): Found 2 nodes of 4. Limit used: 5. Using Inode routines
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 5; storage space: 14 unneeded,2 used
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 1
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 1
[0] <mat:seqaij> MatCheckCompressedRow(): Found the ratio (num_zerorows 2)/(num_localrows 4) < 0.6. Do not use CompressedRow routines.
[0] <mat:seqaij> MatSeqAIJCheckInode(): Found 4 nodes out of 4 rows. Not using Inode routines
4×5 GridapPETSc.PETScMatrix:
 0.0  0.0  5.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  7.0
 0.0  0.0  0.0  0.0  0.0
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Matrix size: 3 X 2; storage space: 6 unneeded,0 used
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 0
[0] <mat:seqaij> MatCheckCompressedRow(): Found the ratio (num_zerorows 3)/(num_localrows 3) > 0.6. Use CompressedRow routines.
[0] <mat:seqaij> MatSeqAIJCheckInode(): Found 1 nodes of 3. Limit used: 5. Using Inode routines
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 4; storage space: 0 unneeded,10 used
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 3
[0] <mat:seqaij> MatCheckCompressedRow(): Found the ratio (num_zerorows 0)/(num_localrows 4) < 0.6. Do not use CompressedRow routines.
[0] <mat:seqaij> MatSeqAIJCheckInode(): Found 4 nodes out of 4 rows. Not using Inode routines
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <mat:seqaij> MatConvert(): Calling duplicate for initial matrix seqaij 0 1
[0] <mat:seqaij> MatConvert(): Calling duplicate for initial matrix seqaij 0 1
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> Petsc_OuterComm_Attr_DeleteFn(): Removing reference to PETSc communicator embedded in a user MPI_Comm -2080374784
[0] <sys> Petsc_InnerComm_Attr_DeleteFn(): User MPI_Comm 1140850689 is being unlinked from inner PETSc comm -2080374784
[0] <sys> PetscCommDestroy(): Deleting PETSc MPI_Comm -2080374784
[0] <sys> Petsc_Counter_Attr_DeleteFn(): Deleting counter data in an MPI_Comm -2080374784
[0] <sys> PetscFinalize(): PetscFinalize() called
  0.687266 seconds (1.66 M allocations: 109.182 MiB, 10.52% gc time, 87.49% compilation time: 2% of which was recompilation)
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
KSP Object: 1 MPI process
  type: gmres
    restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
    happy breakdown tolerance 1e-30
  maximum iterations=10000, initial guess is zero
  tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
  left preconditioning
  using DEFAULT norm type for convergence test
PC Object: 1 MPI process
  type: jacobi
  PC has not been set up so information may be incomplete
    type DIAGONAL
  linear system matrix = precond matrix:
  Mat Object: 1 MPI process
    type: seqaij
    rows=4, cols=4
    total: nonzeros=10, allocated nonzeros=0
    total number of mallocs used during MatSetValues calls=0
      not using I-node routines
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0 KSP Residual norm 2.000000000000e+00
  1 KSP Residual norm 5.087681048628e-16
  0.762290 seconds (2.21 M allocations: 150.457 MiB, 16.52% gc time, 80.75% compilation time)
  0 SNES Function norm 3.605551275464e+00
  1 SNES Function norm 4.444444444444e-01
  2 SNES Function norm 7.111111111111e-02
  3 SNES Function norm 3.936947327951e-03
  4 SNES Function norm 1.525925473445e-05
  5 SNES Function norm 2.328306437081e-10
  6 SNES Function norm 0.000000000000e+00
  Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 6
  0 SNES Function norm 0.000000000000e+00
  1 SNES Function norm 0.000000000000e+00
  Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 1
  0 SNES Function norm 0.000000000000e+00
  1 SNES Function norm 0.000000000000e+00
  Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 1
  0 SNES Function norm 1.486606874732e-01
  1 SNES Function norm 8.402777777778e-03
  2 SNES Function norm 6.831067663990e-05
  3 SNES Function norm 4.665073682466e-09
  4 SNES Function norm 0.000000000000e+00
  Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 4
  0 SNES Function norm 0.000000000000e+00
  1 SNES Function norm 0.000000000000e+00
  Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 1
  0 SNES Function norm 0.000000000000e+00
  1 SNES Function norm 0.000000000000e+00
  Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 1
  0 SNES Function norm 3.605551275464e+00
  1 SNES Function norm 4.444444444444e-01
  2 SNES Function norm 7.111111111111e-02
  3 SNES Function norm 3.936947327951e-03
  4 SNES Function norm 1.525925473445e-05
  5 SNES Function norm 2.328306437081e-10
  6 SNES Function norm 0.000000000000e+00
  Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 6
  0.291578 seconds (1.10 M allocations: 66.008 MiB, 22.17% gc time, 77.34% compilation time)
[0] <sys> PetscDetermineInitialFPTrap(): Floating point trapping is off by default 0
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDeviceType host available, initializing
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDevice host initialized, default device id 0, view FALSE, init type lazy
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDeviceType cuda not available
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDeviceType hip not available
[0] <sys> PetscDeviceInitializeTypeFromOptions_Private(): PetscDeviceType sycl not available
[0] <sys> PetscInitialize_Common(): PETSc successfully started: number of processors = 1
[0] <sys> PetscGetHostName(): Rejecting domainname, likely is NIS cdb4b9906329.(none)
[0] <sys> PetscInitialize_Common(): Running on machine: cdb4b9906329
[0] <sys> PetscCommDuplicate(): Duplicating a communicator 1140850689 -2080374784 max tags = 1073741823
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 3; storage space: 2 unneeded,1 used
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 1
[0] <mat:seqaij> MatCheckCompressedRow(): Found the ratio (num_zerorows 3)/(num_localrows 4) > 0.6. Use CompressedRow routines.
[0] <mat:seqaij> MatSeqAIJCheckInode(): Found 2 nodes of 4. Limit used: 5. Using Inode routines
4×3 GridapPETSc.PETScMatrix:
 -4.0  0.0  0.0
  0.0  0.0  0.0
  0.0  0.0  0.0
  0.0  0.0  0.0
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 3; storage space: 11 unneeded,1 used
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 1
[0] <mat:seqaij> MatCheckCompressedRow(): Found the ratio (num_zerorows 3)/(num_localrows 4) > 0.6. Use CompressedRow routines.
[0] <mat:seqaij> MatSeqAIJCheckInode(): Found 2 nodes of 4. Limit used: 5. Using Inode routines
4×3 GridapPETSc.PETScMatrix:
 -4.0  0.0  0.0
  0.0  0.0  0.0
  0.0  0.0  0.0
  0.0  0.0  0.0
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Matrix size: 4 X 3; storage space: 0 unneeded,1 used
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
[0] <mat:seqaij> MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 1
[0] <mat:seqaij> MatCheckCompressedRow(): Found the ratio (num_zerorows 3)/(num_localrows 4) > 0.6. Use CompressedRow routines.
[0] <mat:seqaij> MatSeqAIJCheckInode(): Found 2 nodes of 4. Limit used: 5. Using Inode routines
4×3 GridapPETSc.PETScMatrix:
 -2.0  0.0  0.0
  0.0  0.0  0.0
  0.0  0.0  0.0
  0.0  0.0  0.0
[0] <mat:seqaij> MatConvert(): Calling duplicate for initial matrix seqaij 0 1
[0] <mat:seqaij> MatConvert(): Calling duplicate for initial matrix seqaij 0 1
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
4-element GridapPETSc.PETScVector:
 6.0
 0.0
 0.0
 1.0
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
[0] <sys> PetscCommDuplicate(): Using internal PETSc communicator 1140850689 -2080374784
┌ Warning: 1 objects still not finalized before calling GridapPETSc.Finalize()
└ @ GridapPETSc /shared/src/Environment.jl:28
[0] <sys> PetscFinalize(): PetscFinalize() called
  0.533412 seconds (1.06 M allocations: 70.173 MiB, 12.53% gc time, 85.19% compilation time: 2% of which was recompilation)
  0 KSP Residual norm 0.0467654
  1 KSP Residual norm 0.015417
  2 KSP Residual norm 0.00327706
  3 KSP Residual norm 0.000661172
  4 KSP Residual norm 0.000252898
  5 KSP Residual norm 0.00014497
  6 KSP Residual norm 7.44567e-05
  7 KSP Residual norm 5.31437e-05
  8 KSP Residual norm 3.10604e-05
  9 KSP Residual norm 1.88474e-05
 10 KSP Residual norm 1.67308e-05
 11 KSP Residual norm 1.30481e-05
 12 KSP Residual norm 8.92208e-06
 13 KSP Residual norm 6.2216e-06
 14 KSP Residual norm 5.78002e-06
 15 KSP Residual norm 4.40273e-06
 16 KSP Residual norm 4.00261e-06
 17 KSP Residual norm 2.70432e-06
 18 KSP Residual norm 2.34576e-06
 19 KSP Residual norm 1.94042e-06
 20 KSP Residual norm 1.75753e-06
 21 KSP Residual norm 1.73547e-06
 22 KSP Residual norm 1.62163e-06
 23 KSP Residual norm 1.25495e-06
 24 KSP Residual norm 1.01893e-06
 25 KSP Residual norm 8.34647e-07
 26 KSP Residual norm 6.48088e-07
 27 KSP Residual norm 5.14953e-07
 28 KSP Residual norm 4.21736e-07
 29 KSP Residual norm 3.82565e-07
 30 KSP Residual norm 3.11746e-07
 31 KSP Residual norm 2.49033e-07
 32 KSP Residual norm 2.33299e-07
 33 KSP Residual norm 2.07937e-07
 34 KSP Residual norm 1.80063e-07
 35 KSP Residual norm 1.38409e-07
 36 KSP Residual norm 1.20657e-07
 37 KSP Residual norm 9.80194e-08
 38 KSP Residual norm 7.25573e-08
 39 KSP Residual norm 4.91734e-08
 40 KSP Residual norm 3.75952e-08
 41 KSP Residual norm 2.78836e-08
 42 KSP Residual norm 2.23736e-08
 43 KSP Residual norm 1.57428e-08
 44 KSP Residual norm 1.24789e-08
 45 KSP Residual norm 9.28278e-09
 46 KSP Residual norm 6.0542e-09
 47 KSP Residual norm 4.92096e-09
 48 KSP Residual norm 3.61052e-09
 49 KSP Residual norm 3.1137e-09
 50 KSP Residual norm 1.99343e-09
 51 KSP Residual norm 1.768e-09
 52 KSP Residual norm 1.32989e-09
 53 KSP Residual norm 9.447e-10
 54 KSP Residual norm 6.254e-10
 55 KSP Residual norm 4.207e-10
  Linear solve converged due to CONVERGED_RTOL iterations 55
WARNING! There are options you set that were not used!
WARNING! could be spelling mistake, etc!
There is one unused database option. It is:
Option left: name:-mg_levels_esteig_ksp_type value: cg source: command line
 11.962318 seconds (64.14 M allocations: 3.811 GiB, 6.82% gc time, 98.35% compilation time: <1% of which was recompilation)
[ Info: Skipping DarcyDriver since petsc is not configured with mumps.
WARNING! There are options you set that were not used!
WARNING! could be spelling mistake, etc!
There are 5 unused database options. They are:
Option left: name:-ksp_converged_reason (no value) source: command line
Option left: name:-ksp_monitor (no value) source: command line
Option left: name:-ksp_type value: preonly source: command line
Option left: name:-pc_factor_mat_solver_type value: mumps source: command line
Option left: name:-pc_type value: lu source: command line
  1.716903 seconds (13.33 M allocations: 761.656 MiB, 13.34% gc time, 94.11% compilation time)
  0 SNES Function norm 2.409822369424e+06
    Linear solve converged due to CONVERGED_RTOL iterations 54
  1 SNES Function norm 8.075649416004e+00
    Linear solve converged due to CONVERGED_RTOL iterations 39
  2 SNES Function norm 4.662170753064e-01
    Linear solve converged due to CONVERGED_RTOL iterations 37
  3 SNES Function norm 8.399998666393e-03
    Linear solve converged due to CONVERGED_RTOL iterations 37
  4 SNES Function norm 4.665302403789e-06
    Linear solve converged due to CONVERGED_RTOL iterations 44
  5 SNES Function norm 1.574162255866e-11
  Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 5
  0 SNES Function norm 2.409822369424e+06
    Linear solve converged due to CONVERGED_RTOL iterations 54
  1 SNES Function norm 8.075649416004e+00
    Linear solve converged due to CONVERGED_RTOL iterations 39
  2 SNES Function norm 4.662170753064e-01
    Linear solve converged due to CONVERGED_RTOL iterations 37
  3 SNES Function norm 8.399998666393e-03
    Linear solve converged due to CONVERGED_RTOL iterations 37
  4 SNES Function norm 4.665302403789e-06
    Linear solve converged due to CONVERGED_RTOL iterations 44
  5 SNES Function norm 1.574162255866e-11
  Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 5
  7.012252 seconds (31.47 M allocations: 1.894 GiB, 6.38% gc time, 96.02% compilation time)
  0 KSP Residual norm 8.550000000000e-03
  1 KSP Residual norm 8.968352924103e-04
  2 KSP Residual norm 9.188071216687e-05
  3 KSP Residual norm 7.483127648168e-06
  4 KSP Residual norm 6.216337456339e-07
  5 KSP Residual norm 5.262981415328e-08
  6 KSP Residual norm 4.447870837457e-09
  7 KSP Residual norm 3.660520650081e-10
  8 KSP Residual norm 3.000628543014e-11
  9 KSP Residual norm 2.545610900010e-12
 10 KSP Residual norm 2.084997771778e-13
  Linear solve converged due to CONVERGED_RTOL iterations 10
KSP Object: 1 MPI process
  type: cg
  maximum iterations=1000, initial guess is zero
  tolerances: relative=1e-10, absolute=1e-50, divergence=10000.
  left preconditioning
  using UNPRECONDITIONED norm type for convergence test
PC Object: 1 MPI process
  type: gamg
    type is MULTIPLICATIVE, levels=3 cycles=v
      Cycles per PCApply=1
      Using externally compute Galerkin coarse grid matrices
      GAMG specific options
        Threshold for dropping small values in graph on each level =   -1.   -1.   -1.  
        Threshold scaling factor for each level not specified = 1.
        AGG specific options
          Number of levels of aggressive coarsening 0
          MatCoarsen Object: (pc_gamg_) 1 MPI process
            type: misk
          Number smoothing steps to construct prolongation 1
        Complexity:    grid = 1.11385    operator = 1.15878
        Per-level complexity: op = operator, int = interpolation
            #equations  | #active PEs | avg nnz/row op | avg nnz/row int
                  7            1              7                0
                 76            1             32                4
                729            1             22                6
  Coarse grid solver -- level 0 -------------------------------
    KSP Object: (mg_coarse_) 1 MPI process
      type: preonly
      maximum iterations=10000, initial guess is zero
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object: (mg_coarse_) 1 MPI process
      type: bjacobi
        number of blocks = 1
        Local solver information for first block is in the following KSP and PC objects on rank 0:
        Use -mg_coarse_ksp_view ::ascii_info_detail to display information for all blocks
        KSP Object: (mg_coarse_sub_) 1 MPI process
          type: preonly
          maximum iterations=1, initial guess is zero
          tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
          left preconditioning
          using NONE norm type for convergence test
        PC Object: (mg_coarse_sub_) 1 MPI process
          type: cholesky
            out-of-place factorization
            tolerance for zero pivot 2.22045e-14
            matrix ordering: nd
            factor fill ratio given 5., needed 1.
              Factored matrix follows:
                Mat Object: (mg_coarse_sub_) 1 MPI process
                  type: seqsbaij
                  rows=7, cols=7
                  package used to perform factorization: petsc
                  total: nonzeros=28, allocated nonzeros=28
                      block size is 1
          linear system matrix = precond matrix:
          Mat Object: (mg_coarse_sub_) 1 MPI process
            type: seqaij
            rows=7, cols=7
            total: nonzeros=49, allocated nonzeros=49
            total number of mallocs used during MatSetValues calls=0
              using I-node routines: found 2 nodes, limit used is 5
      linear system matrix = precond matrix:
      Mat Object: (mg_coarse_sub_) 1 MPI process
        type: seqaij
        rows=7, cols=7
        total: nonzeros=49, allocated nonzeros=49
        total number of mallocs used during MatSetValues calls=0
          using I-node routines: found 2 nodes, limit used is 5
  Down solver (pre-smoother) on level 1 -------------------------------
    KSP Object: (mg_levels_1_) 1 MPI process
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.255929, max 2.81522
        eigenvalues provided (min 0.325601, max 2.55929) with transform: [0. 0.1; 0. 1.1]
      maximum iterations=2, nonzero initial guess
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object: (mg_levels_1_) 1 MPI process
      type: jacobi
        type DIAGONAL
      linear system matrix = precond matrix:
      Mat Object: 1 MPI process
        type: seqaij
        rows=76, cols=76
        total: nonzeros=2432, allocated nonzeros=2432
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  Up solver (post-smoother) same as down solver (pre-smoother)
  Down solver (pre-smoother) on level 2 -------------------------------
    KSP Object: (mg_levels_2_) 1 MPI process
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.143003, max 1.57304
        eigenvalues provided (min 0.109061, max 1.43003) with transform: [0. 0.1; 0. 1.1]
      maximum iterations=2, nonzero initial guess
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object: (mg_levels_2_) 1 MPI process
      type: jacobi
        type DIAGONAL
      linear system matrix = precond matrix:
      Mat Object: 1 MPI process
        type: seqaij
        rows=729, cols=729
        total: nonzeros=15625, allocated nonzeros=0
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  Up solver (post-smoother) same as down solver (pre-smoother)
  linear system matrix = precond matrix:
  Mat Object: 1 MPI process
    type: seqaij
    rows=729, cols=729
    total: nonzeros=15625, allocated nonzeros=0
    total number of mallocs used during MatSetValues calls=0
      not using I-node routines
  0 KSP Residual norm 8.550000000000e-03
  1 KSP Residual norm 8.968352924103e-04
  2 KSP Residual norm 9.188071216687e-05
  3 KSP Residual norm 7.483127648168e-06
  4 KSP Residual norm 6.216337456339e-07
  5 KSP Residual norm 5.262981415328e-08
  6 KSP Residual norm 4.447870837457e-09
  7 KSP Residual norm 3.660520650081e-10
  8 KSP Residual norm 3.000628543014e-11
  9 KSP Residual norm 2.545610900010e-12
 10 KSP Residual norm 2.084997771778e-13
  Linear solve converged due to CONVERGED_RTOL iterations 10
KSP Object: 1 MPI process
  type: cg
  maximum iterations=1000, initial guess is zero
  tolerances: relative=1e-10, absolute=1e-50, divergence=10000.
  left preconditioning
  using UNPRECONDITIONED norm type for convergence test
PC Object: 1 MPI process
  type: gamg
    type is MULTIPLICATIVE, levels=3 cycles=v
      Cycles per PCApply=1
      Using externally compute Galerkin coarse grid matrices
      GAMG specific options
        Threshold for dropping small values in graph on each level =   -1.   -1.   -1.  
        Threshold scaling factor for each level not specified = 1.
        AGG specific options
          Number of levels of aggressive coarsening 0
          MatCoarsen Object: (pc_gamg_) 1 MPI process
            type: misk
          Number smoothing steps to construct prolongation 1
        Complexity:    grid = 1.11385    operator = 1.15878
        Per-level complexity: op = operator, int = interpolation
            #equations  | #active PEs | avg nnz/row op | avg nnz/row int
                  7            1              7                0
                 76            1             32                4
                729            1             22                6
  Coarse grid solver -- level 0 -------------------------------
    KSP Object: (mg_coarse_) 1 MPI process
      type: preonly
      maximum iterations=10000, initial guess is zero
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object: (mg_coarse_) 1 MPI process
      type: bjacobi
        number of blocks = 1
        Local solver information for first block is in the following KSP and PC objects on rank 0:
        Use -mg_coarse_ksp_view ::ascii_info_detail to display information for all blocks
        KSP Object: (mg_coarse_sub_) 1 MPI process
          type: preonly
          maximum iterations=1, initial guess is zero
          tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
          left preconditioning
          using NONE norm type for convergence test
        PC Object: (mg_coarse_sub_) 1 MPI process
          type: cholesky
            out-of-place factorization
            tolerance for zero pivot 2.22045e-14
            matrix ordering: nd
            factor fill ratio given 5., needed 1.
              Factored matrix follows:
                Mat Object: (mg_coarse_sub_) 1 MPI process
                  type: seqsbaij
                  rows=7, cols=7
                  package used to perform factorization: petsc
                  total: nonzeros=28, allocated nonzeros=28
                      block size is 1
          linear system matrix = precond matrix:
          Mat Object: (mg_coarse_sub_) 1 MPI process
            type: seqaij
            rows=7, cols=7
            total: nonzeros=49, allocated nonzeros=49
            total number of mallocs used during MatSetValues calls=0
              using I-node routines: found 2 nodes, limit used is 5
      linear system matrix = precond matrix:
      Mat Object: (mg_coarse_sub_) 1 MPI process
        type: seqaij
        rows=7, cols=7
        total: nonzeros=49, allocated nonzeros=49
        total number of mallocs used during MatSetValues calls=0
          using I-node routines: found 2 nodes, limit used is 5
  Down solver (pre-smoother) on level 1 -------------------------------
    KSP Object: (mg_levels_1_) 1 MPI process
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.255929, max 2.81522
        eigenvalues provided (min 0.325601, max 2.55929) with transform: [0. 0.1; 0. 1.1]
      maximum iterations=2, nonzero initial guess
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object: (mg_levels_1_) 1 MPI process
      type: jacobi
        type DIAGONAL
      linear system matrix = precond matrix:
      Mat Object: 1 MPI process
        type: seqaij
        rows=76, cols=76
        total: nonzeros=2432, allocated nonzeros=2432
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  Up solver (post-smoother) same as down solver (pre-smoother)
  Down solver (pre-smoother) on level 2 -------------------------------
    KSP Object: (mg_levels_2_) 1 MPI process
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.143003, max 1.57304
        eigenvalues provided (min 0.109061, max 1.43003) with transform: [0. 0.1; 0. 1.1]
      maximum iterations=2, nonzero initial guess
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object: (mg_levels_2_) 1 MPI process
      type: jacobi
        type DIAGONAL
      linear system matrix = precond matrix:
      Mat Object: 1 MPI process
        type: seqaij
        rows=729, cols=729
        total: nonzeros=15625, allocated nonzeros=0
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  Up solver (post-smoother) same as down solver (pre-smoother)
  linear system matrix = precond matrix:
  Mat Object: 1 MPI process
    type: seqaij
    rows=729, cols=729
    total: nonzeros=15625, allocated nonzeros=0
    total number of mallocs used during MatSetValues calls=0
      not using I-node routines
  0 KSP Residual norm 8.550000000000e-03
  1 KSP Residual norm 8.968352924103e-04
  2 KSP Residual norm 9.188071216687e-05
  3 KSP Residual norm 7.483127648168e-06
  4 KSP Residual norm 6.216337456339e-07
  5 KSP Residual norm 5.262981415328e-08
  6 KSP Residual norm 4.447870837457e-09
  7 KSP Residual norm 3.660520650081e-10
  8 KSP Residual norm 3.000628543014e-11
  9 KSP Residual norm 2.545610900010e-12
 10 KSP Residual norm 2.084997771778e-13
  Linear solve converged due to CONVERGED_RTOL iterations 10
KSP Object: 1 MPI process
  type: cg
  maximum iterations=1000, initial guess is zero
  tolerances: relative=1e-10, absolute=1e-50, divergence=10000.
  left preconditioning
  using UNPRECONDITIONED norm type for convergence test
PC Object: 1 MPI process
  type: gamg
    type is MULTIPLICATIVE, levels=3 cycles=v
      Cycles per PCApply=1
      Using externally compute Galerkin coarse grid matrices
      GAMG specific options
        Threshold for dropping small values in graph on each level =   -1.   -1.   -1.  
        Threshold scaling factor for each level not specified = 1.
        AGG specific options
          Number of levels of aggressive coarsening 0
          MatCoarsen Object: (pc_gamg_) 1 MPI process
            type: misk
          Number smoothing steps to construct prolongation 1
        Complexity:    grid = 1.11385    operator = 1.15878
        Per-level complexity: op = operator, int = interpolation
            #equations  | #active PEs | avg nnz/row op | avg nnz/row int
                  7            1              7                0
                 76            1             32                4
                729            1             22                6
  Coarse grid solver -- level 0 -------------------------------
    KSP Object: (mg_coarse_) 1 MPI process
      type: preonly
      maximum iterations=10000, initial guess is zero
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object: (mg_coarse_) 1 MPI process
      type: bjacobi
        number of blocks = 1
        Local solver information for first block is in the following KSP and PC objects on rank 0:
        Use -mg_coarse_ksp_view ::ascii_info_detail to display information for all blocks
        KSP Object: (mg_coarse_sub_) 1 MPI process
          type: preonly
          maximum iterations=1, initial guess is zero
          tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
          left preconditioning
          using NONE norm type for convergence test
        PC Object: (mg_coarse_sub_) 1 MPI process
          type: cholesky
            out-of-place factorization
            tolerance for zero pivot 2.22045e-14
            matrix ordering: nd
            factor fill ratio given 5., needed 1.
              Factored matrix follows:
                Mat Object: (mg_coarse_sub_) 1 MPI process
                  type: seqsbaij
                  rows=7, cols=7
                  package used to perform factorization: petsc
                  total: nonzeros=28, allocated nonzeros=28
                      block size is 1
          linear system matrix = precond matrix:
          Mat Object: (mg_coarse_sub_) 1 MPI process
            type: seqaij
            rows=7, cols=7
            total: nonzeros=49, allocated nonzeros=49
            total number of mallocs used during MatSetValues calls=0
              using I-node routines: found 2 nodes, limit used is 5
      linear system matrix = precond matrix:
      Mat Object: (mg_coarse_sub_) 1 MPI process
        type: seqaij
        rows=7, cols=7
        total: nonzeros=49, allocated nonzeros=49
        total number of mallocs used during MatSetValues calls=0
          using I-node routines: found 2 nodes, limit used is 5
  Down solver (pre-smoother) on level 1 -------------------------------
    KSP Object: (mg_levels_1_) 1 MPI process
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.255929, max 2.81522
        eigenvalues provided (min 0.325601, max 2.55929) with transform: [0. 0.1; 0. 1.1]
      maximum iterations=2, nonzero initial guess
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object: (mg_levels_1_) 1 MPI process
      type: jacobi
        type DIAGONAL
      linear system matrix = precond matrix:
      Mat Object: 1 MPI process
        type: seqaij
        rows=76, cols=76
        total: nonzeros=2432, allocated nonzeros=2432
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  Up solver (post-smoother) same as down solver (pre-smoother)
  Down solver (pre-smoother) on level 2 -------------------------------
    KSP Object: (mg_levels_2_) 1 MPI process
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.143003, max 1.57304
        eigenvalues provided (min 0.109061, max 1.43003) with transform: [0. 0.1; 0. 1.1]
      maximum iterations=2, nonzero initial guess
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object: (mg_levels_2_) 1 MPI process
      type: jacobi
        type DIAGONAL
      linear system matrix = precond matrix:
      Mat Object: 1 MPI process
        type: seqaij
        rows=729, cols=729
        total: nonzeros=15625, allocated nonzeros=39304
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  Up solver (post-smoother) same as down solver (pre-smoother)
  linear system matrix = precond matrix:
  Mat Object: 1 MPI process
    type: seqaij
    rows=729, cols=729
    total: nonzeros=15625, allocated nonzeros=39304
    total number of mallocs used during MatSetValues calls=0
      not using I-node routines
  0 KSP Residual norm 8.550000000000e-03
  1 KSP Residual norm 8.968352924103e-04
  2 KSP Residual norm 9.188071216687e-05
  3 KSP Residual norm 7.483127648168e-06
  4 KSP Residual norm 6.216337456339e-07
  5 KSP Residual norm 5.262981415328e-08
  6 KSP Residual norm 4.447870837457e-09
  7 KSP Residual norm 3.660520650081e-10
  8 KSP Residual norm 3.000628543014e-11
  9 KSP Residual norm 2.545610900010e-12
 10 KSP Residual norm 2.084997771778e-13
  Linear solve converged due to CONVERGED_RTOL iterations 10
KSP Object: 1 MPI process
  type: cg
  maximum iterations=1000, initial guess is zero
  tolerances: relative=1e-10, absolute=1e-50, divergence=10000.
  left preconditioning
  using UNPRECONDITIONED norm type for convergence test
PC Object: 1 MPI process
  type: gamg
    type is MULTIPLICATIVE, levels=3 cycles=v
      Cycles per PCApply=1
      Using externally compute Galerkin coarse grid matrices
      GAMG specific options
        Threshold for dropping small values in graph on each level =   -1.   -1.   -1.  
        Threshold scaling factor for each level not specified = 1.
        AGG specific options
          Number of levels of aggressive coarsening 0
          MatCoarsen Object: (pc_gamg_) 1 MPI process
            type: misk
          Number smoothing steps to construct prolongation 1
        Complexity:    grid = 1.11385    operator = 1.15878
        Per-level complexity: op = operator, int = interpolation
            #equations  | #active PEs | avg nnz/row op | avg nnz/row int
                  7            1              7                0
                 76            1             32                4
                729            1             22                6
  Coarse grid solver -- level 0 -------------------------------
    KSP Object: (mg_coarse_) 1 MPI process
      type: preonly
      maximum iterations=10000, initial guess is zero
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object: (mg_coarse_) 1 MPI process
      type: bjacobi
        number of blocks = 1
        Local solver information for first block is in the following KSP and PC objects on rank 0:
        Use -mg_coarse_ksp_view ::ascii_info_detail to display information for all blocks
        KSP Object: (mg_coarse_sub_) 1 MPI process
          type: preonly
          maximum iterations=1, initial guess is zero
          tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
          left preconditioning
          using NONE norm type for convergence test
        PC Object: (mg_coarse_sub_) 1 MPI process
          type: cholesky
            out-of-place factorization
            tolerance for zero pivot 2.22045e-14
            matrix ordering: nd
            factor fill ratio given 5., needed 1.
              Factored matrix follows:
                Mat Object: (mg_coarse_sub_) 1 MPI process
                  type: seqsbaij
                  rows=7, cols=7
                  package used to perform factorization: petsc
                  total: nonzeros=28, allocated nonzeros=28
                      block size is 1
          linear system matrix = precond matrix:
          Mat Object: (mg_coarse_sub_) 1 MPI process
            type: seqaij
            rows=7, cols=7
            total: nonzeros=49, allocated nonzeros=49
            total number of mallocs used during MatSetValues calls=0
              using I-node routines: found 2 nodes, limit used is 5
      linear system matrix = precond matrix:
      Mat Object: (mg_coarse_sub_) 1 MPI process
        type: seqaij
        rows=7, cols=7
        total: nonzeros=49, allocated nonzeros=49
        total number of mallocs used during MatSetValues calls=0
          using I-node routines: found 2 nodes, limit used is 5
  Down solver (pre-smoother) on level 1 -------------------------------
    KSP Object: (mg_levels_1_) 1 MPI process
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.255929, max 2.81522
        eigenvalues provided (min 0.325601, max 2.55929) with transform: [0. 0.1; 0. 1.1]
      maximum iterations=2, nonzero initial guess
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object: (mg_levels_1_) 1 MPI process
      type: jacobi
        type DIAGONAL
      linear system matrix = precond matrix:
      Mat Object: 1 MPI process
        type: seqaij
        rows=76, cols=76
        total: nonzeros=2432, allocated nonzeros=2432
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  Up solver (post-smoother) same as down solver (pre-smoother)
  Down solver (pre-smoother) on level 2 -------------------------------
    KSP Object: (mg_levels_2_) 1 MPI process
      type: chebyshev
        Chebyshev polynomial of first kind
        eigenvalue targets used: min 0.143003, max 1.57304
        eigenvalues provided (min 0.109061, max 1.43003) with transform: [0. 0.1; 0. 1.1]
      maximum iterations=2, nonzero initial guess
      tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
      left preconditioning
      using NONE norm type for convergence test
    PC Object: (mg_levels_2_) 1 MPI process
      type: jacobi
        type DIAGONAL
      linear system matrix = precond matrix:
      Mat Object: 1 MPI process
        type: seqaij
        rows=729, cols=729
        total: nonzeros=15625, allocated nonzeros=39304
        total number of mallocs used during MatSetValues calls=0
          not using I-node routines
  Up solver (post-smoother) same as down solver (pre-smoother)
  linear system matrix = precond matrix:
  Mat Object: 1 MPI process
    type: seqaij
    rows=729, cols=729
    total: nonzeros=15625, allocated nonzeros=39304
    total number of mallocs used during MatSetValues calls=0
      not using I-node routines
WARNING! There are options you set that were not used!
WARNING! could be spelling mistake, etc!
There is one unused database option. It is:
Option left: name:-mg_levels_esteig_ksp_type value: cg source: command line
  2.360171 seconds (7.65 M allocations: 513.690 MiB, 7.71% gc time, 93.44% compilation time)
Test Summary: | Pass  Total   Time
SERIAL        |  130    130  28.1s
 28.083266 seconds (132.14 M allocations: 8.085 GiB, 7.54% gc time, 89.08% compilation time: <1% of which was recompilation)
[1, 2, 3, 5, 6]
[4, 5, 7, 3, 6]
[6, 7, 4]
Vec Object: 1 MPI process
  type: seq
10.
20.
30.
40.
50.
60.
70.
3-element PartitionedArrays.DebugArray{SparseArrays.SparseMatrixCSC{Float64, Int64}, 1}:
[1] = sparse([1, 2, 3, 1, 3], [1, 2, 3, 4, 5], [9.0, 9.0, 9.0, 1.0, 1.0], 5, 5)
[2] = sparse([1, 2, 2, 2, 1], [1, 2, 3, 4, 5], [9.0, 9.0, 1.0, 9.0, 1.0], 5, 5)
[3] = sparse([1, 2, 1], [1, 2, 3], [9.0, 9.0, 1.0], 3, 3)

3-element PartitionedArrays.DebugArray{SparseArrays.SparseMatrixCSC{Float64, Int64}, 1}:
[1] = sparse([1, 2, 3, 5, 4, 6, 1, 5, 3, 4, 6, 5, 7], [1, 2, 3, 3, 4, 4, 5, 5, 6, 6, 6, 7, 7], [9.0, 9.0, 9.0, 9.0, 9.0, 1.0, 1.0, 9.0, 1.0, 1.0, 9.0, 1.0, 9.0], 7, 7)
[2] = sparse(Int64[], Int64[], Float64[], 2, 2)
[3] = sparse(Int64[], Int64[], Float64[], 2, 2)

Mat Object: 1 MPI process
  type: seqaij
row 0: (0, 9.)  (4, 1.) 
row 1: (1, 9.) 
row 2: (2, 9.)  (5, 1.) 
row 3: (3, 9.)  (5, 1.) 
row 4: (2, 9.)  (4, 9.)  (6, 1.) 
row 5: (3, 1.)  (5, 9.) 
row 6: (6, 9.) 
  Linear solve converged due to CONVERGED_RTOL iterations 5
Vec Object: 1 MPI process
  type: seq
10.
20.
30.
40.
50.
60.
70.
Vec Object: 1 MPI process
  type: seq
140.
180.
330.
420.
790.
580.
630.
  Linear solve converged due to CONVERGED_RTOL iterations 5
Vec Object: 1 MPI process
  type: seq
140.
180.
330.
420.
790.
580.
630.
Vec Object: 1 MPI process
  type: seq
10.
20.
30.
40.
50.
60.
70.
Vec Object: 1 MPI process
  type: seq
10.
20.
30.
40.
50.
60.
70.
  Linear solve converged due to CONVERGED_RTOL iterations 5
Vec Object: 1 MPI process
  type: seq
10.
20.
30.
40.
50.
60.
70.
Vec Object: 1 MPI process
  type: seq
140.
180.
330.
420.
790.
580.
630.
  Linear solve converged due to CONVERGED_RTOL iterations 5
Vec Object: 1 MPI process
  type: seq
140.
180.
330.
420.
790.
580.
630.
Vec Object: 1 MPI process
  type: seq
10.
20.
30.
40.
50.
60.
70.
Vec Object: 1 MPI process
  type: seq
10.
20.
30.
40.
50.
60.
70.
 31.278373 seconds (40.54 M allocations: 2.251 GiB, 2.59% gc time, 27.62% compilation time)
  Linear solve converged due to CONVERGED_RTOL iterations 28
 30.172800 seconds (97.37 M allocations: 5.752 GiB, 6.35% gc time, 71.58% compilation time: <1% of which was recompilation)
  0 SNES Function norm 2.409822369424e+06
    Linear solve converged due to CONVERGED_RTOL iterations 258
  1 SNES Function norm 8.077651079465e+00
    Linear solve converged due to CONVERGED_RTOL iterations 225
  2 SNES Function norm 4.661493250862e-01
    Linear solve converged due to CONVERGED_RTOL iterations 215
  3 SNES Function norm 8.397548297118e-03
    Linear solve converged due to CONVERGED_RTOL iterations 246
  4 SNES Function norm 4.669108166348e-06
    Linear solve converged due to CONVERGED_RTOL iterations 313
  5 SNES Function norm 4.635681940158e-11
  Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 5
  0 SNES Function norm 4.635681940158e-11
    Linear solve converged due to CONVERGED_RTOL iterations 287
  1 SNES Function norm 5.130177567360e-13
  Nonlinear solve converged due to CONVERGED_SNORM_RELATIVE iterations 1
  0 SNES Function norm 2.409822369424e+06
    Linear solve converged due to CONVERGED_RTOL iterations 258
  1 SNES Function norm 8.077651079465e+00
    Linear solve converged due to CONVERGED_RTOL iterations 225
  2 SNES Function norm 4.661493250862e-01
    Linear solve converged due to CONVERGED_RTOL iterations 215
  3 SNES Function norm 8.397548297114e-03
    Linear solve converged due to CONVERGED_RTOL iterations 246
  4 SNES Function norm 4.669108165844e-06
    Linear solve converged due to CONVERGED_RTOL iterations 313
  5 SNES Function norm 4.635679952061e-11
  Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 5
  0 SNES Function norm 4.635679952061e-11
    Linear solve converged due to CONVERGED_RTOL iterations 287
  1 SNES Function norm 5.117078090188e-13
  Nonlinear solve converged due to CONVERGED_SNORM_RELATIVE iterations 1
 30.713103 seconds (22.31 M allocations: 1.437 GiB, 2.42% gc time, 18.70% compilation time)
Test Summary: | Pass  Total     Time
SEQUENTIAL    |   60     60  1m32.3s
 92.246376 seconds (160.30 M allocations: 9.444 GiB, 3.76% gc time, 39.08% compilation time: <1% of which was recompilation)
┌ Warning: mpiexec() is deprecated, use the non-do-block form
│   caller = ip:0x0
└ @ Core :-1
[1, 2, 3, 5, 6]
[6, 7, 4]
[4, 5, 7, 3, 6]
Vec Object: 3 MPI processes
  type: mpi
Process [0]
10.
20.
30.
Process [1]
40.
50.
Process [2]
60.
70.
Vec Object: 3 MPI processes
  type: mpi
Process [0]
10.
20.
30.
Process [1]
40.
50.
Process [2]
60.
70.
Vec Object: 3 MPI processes
  type: mpi
Process [0]
10.
20.
30.
Process [1]
40.
50.
Process [2]
60.
70.
3-element MPIArray{SparseArrays.SparseMatrixCSC{Float64, Int64}, 1}:
[1] = sparse([1, 2, 3, 1, 3], [1, 2, 3, 4, 5], [9.0, 9.0, 9.0, 1.0, 1.0], 5, 5)
[2] = sparse([1, 2, 2, 2, 1], [1, 2, 3, 4, 5], [9.0, 9.0, 1.0, 9.0, 1.0], 5, 5)
[3] = sparse([1, 2, 1], [1, 2, 3], [9.0, 9.0, 1.0], 3, 3)



3-element MPIArray{SparseArrays.SparseMatrixCSC{Float64, Int64}, 1}:
[1] = sparse([1, 2, 3, 5, 4, 6, 1, 5, 3, 4, 6, 5, 7], [1, 2, 3, 3, 4, 4, 5, 5, 6, 6, 6, 7, 7], [9.0, 9.0, 9.0, 9.0, 9.0, 1.0, 1.0, 9.0, 1.0, 1.0, 9.0, 1.0, 9.0], 7, 7)
[2] = sparse(Int64[], Int64[], Float64[], 2, 2)
[3] = sparse(Int64[], Int64[], Float64[], 2, 2)



Mat Object: 3 MPI processes
  type: mpiaij
  row 0:   (0, 9.)    (4, 1.)   
  row 1:   (1, 9.)   
  row 2:   (2, 9.)    (5, 1.)   
  row 3:   (3, 9.)    (5, 1.)   
  row 4:   (2, 9.)    (4, 9.)    (6, 1.)   
  row 5:   (3, 1.)    (5, 9.)   
  row 6:   (6, 9.)   
  Linear solve converged due to CONVERGED_RTOL iterations 5
Vec Object: 3 MPI processes
  type: mpi
Process [0]
10.
20.
30.
Process [1]
40.
50.
Process [2]
60.
70.
Vec Object: 3 MPI processes
  type: mpi
Process [0]
140.
180.
330.
Process [1]
420.
790.
Process [2]
580.
630.
  Linear solve converged due to CONVERGED_RTOL iterations 5
Vec Object: 3 MPI processes
  type: mpi
Process [0]
140.
180.
330.
Process [1]
420.
790.
Process [2]
580.
630.
Vec Object: 3 MPI processes
  type: mpi
Process [0]
10.
20.
30.
Process [1]
40.
50.
Process [2]
60.
70.
Vec Object: 3 MPI processes
  type: mpi
Process [0]
10.
20.
30.
Process [1]
40.
50.
Process [2]
60.
70.
  Linear solve converged due to CONVERGED_RTOL iterations 5
Vec Object: 3 MPI processes
  type: mpi
Process [0]
10.
20.
30.
Process [1]
40.
50.
Process [2]
60.
70.
Vec Object: 3 MPI processes
  type: mpi
Process [0]
140.
180.
330.
Process [1]
420.
790.
Process [2]
580.
630.
  Linear solve converged due to CONVERGED_RTOL iterations 5
Vec Object: 3 MPI processes
  type: mpi
Process [0]
140.
180.
330.
Process [1]
420.
790.
Process [2]
580.
630.
Vec Object: 3 MPI processes
  type: mpi
Process [0]
10.
20.
30.
Process [1]
40.
50.
Process [2]
60.
70.
Vec Object: 3 MPI processes
  type: mpi
Process [0]
10.
20.
30.
Process [1]
40.
50.
Process [2]
60.
70.
  9.619973 seconds (538.73 k allocations: 37.581 MiB, 2.94% compilation time)
┌ Error: 
│   exception =
│    User-defined reduction operators are currently not supported on non-Intel architectures.
│    See https://github.com/JuliaParallel/MPI.jl/issues/404 for more details.
│    
│    You may want to use `@RegisterOp` to statically register `f`.
│    
│    Stacktrace:
│      [1] error(s::String)
│        @ Base ./error.jl:35
│      [2] MPI.Op(f::Function, T::Type; iscommutative::Bool)
│        @ MPI ~/.julia/packages/MPI/TKXAj/src/operators.jl:109
│      [3] MPI.Op(f::Function, T::Type)
│        @ MPI ~/.julia/packages/MPI/TKXAj/src/operators.jl:102
│      [4] reduction!(op::PartitionedArrays.var"#and#50", b::MPIArray{Bool, 1}, a::MPIArray{Bool, 1}; destination::Symbol, init::Bool)
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/mpi_array.jl:426
│      [5] reduction(op::Function, a::MPIArray{Bool, 1}; kwargs::Base.Pairs{Symbol, Any, Tuple{Symbol, Symbol}, NamedTuple{(:destination, :init), Tuple{Symbol, Bool}}})
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:517
│      [6] (::PartitionedArrays.var"#is_included#47")(snd_ids_a::MPIArray{Vector{Int32}, 1}, snd_ids_b::MPIArray{Vector{Int32}, 1})
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:606
│      [7] ExchangeGraph_impl_with_neighbors(snd_ids::MPIArray{Vector{Int32}, 1}, neighbors::ExchangeGraph{MPIArray{Vector{Int32}, 1}})
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:612
│      [8] #ExchangeGraph#39
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:592 [inlined]
│      [9] ExchangeGraph
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:585 [inlined]
│     [10] #compute_assembly_neighbors#136
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/p_range.jl:411 [inlined]
│     [11] compute_assembly_neighbors
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/p_range.jl:399 [inlined]
│     [12] assembly_neighbors(indices::MPIArray{OwnAndGhostIndices{Nothing}, 1}; kwargs::Base.Pairs{Symbol, ExchangeGraph{MPIArray{Vector{Int32}, 1}}, Tuple{Symbol}, NamedTuple{(:neighbors,), Tuple{ExchangeGraph{MPIArray{Vector{Int32}, 1}}}}})
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/p_range.jl:386
│     [13] assembly_neighbors
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/p_range.jl:380 [inlined]
│     [14] _find_neighbours!
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:964 [inlined]
│     [15] #_setup_prange_impl_#178
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1249 [inlined]
│     [16] _setup_prange_impl_(ngdofs::Int64, dofs_gids_partition::MPIArray{LocalIndices, 1}, gids_ghost_to_global::MPIArray{Vector{Int64}, 1}, gids_ghost_to_owner::MPIArray{Vector{Int32}, 1})
│        @ GridapDistributed ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1235
│     [17] _setup_prange_with_ghosts(dofs_gids_prange::PRange{MPIArray{LocalIndices, 1}}, gids::MPIArray{Vector{Int64}, 1})
│        @ GridapDistributed ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1197
│     [18] #_setup_prange#165
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1135 [inlined]
│     [19] _setup_prange
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1131 [inlined]
│     [20] _fa_create_from_nz_with_callback
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:559 [inlined]
│     [21] create_from_nz(a::GridapDistributed.DistributedAllocationCOO{FullyAssembledRows, MPIArray{Gridap.Algebra.AllocationCOO{SparseMatrixCSR{0, Float64, Int64}, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}}, Vector{Int64}, Vector{Float64}}, 1}, PRange{MPIArray{LocalIndices, 1}}, PRange{MPIArray{LocalIndices, 1}}}, c_fespace::GridapDistributed.PVectorAllocationTrackOnlyValues{FullyAssembledRows, MPIArray{Vector{Float64}, 1}, PRange{MPIArray{LocalIndices, 1}}})
│        @ GridapDistributed ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:763
│     [22] assemble_matrix_and_vector(a::GridapDistributed.DistributedSparseMatrixAssembler{FullyAssembledRows, MPIArray{Gridap.FESpaces.GenericSparseMatrixAssembler, 1}, GridapDistributed.PSparseMatrixBuilderCOO{SparseMatrixCSR{0, Float64, Int64}, FullyAssembledRows}, GridapDistributed.PVectorBuilder{Vector{Float64}, FullyAssembledRows}, PRange{MPIArray{LocalIndices, 1}}, PRange{MPIArray{LocalIndices, 1}}}, data::MPIArray{Tuple{Tuple{Vector{Any}, Vector{Any}, Vector{Any}}, Tuple{Vector{Any}, Vector{Any}, Vector{Any}}, Tuple{Vector{Any}, Vector{Any}}}, 1})
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/SparseMatrixAssemblers.jl:102
│     [23] residual_and_jacobian(op::Gridap.FESpaces.FEOperatorFromWeakForm, uh::GridapDistributed.DistributedCellField{MPIArray{Gridap.FESpaces.SingleFieldFEFunction{Gridap.CellData.GenericCellField{ReferenceDomain}}, 1}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, CartesianGrid{2, Float64, typeof(identity)}, Gridap.Arrays.IdentityVector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}, GridapDistributed.DistributedFEFunctionData{PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}}})
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/FEOperatorsFromWeakForm.jl:101
│     [24] residual_and_jacobian(op::Gridap.FESpaces.AlgebraicOpFromFEOp, x::PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64})
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/FEOperators.jl:194
│     [25] _setup_cache(x::PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}, nls::PETScNonlinearSolver{typeof(GridapPETSc.snes_from_options)}, op::Gridap.FESpaces.AlgebraicOpFromFEOp)
│        @ GridapPETSc /shared/src/PETScNonlinearSolvers.jl:127
│     [26] solve!(x::PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}, nls::PETScNonlinearSolver{typeof(GridapPETSc.snes_from_options)}, op::Gridap.FESpaces.AlgebraicOpFromFEOp, #unused#::Nothing)
│        @ GridapPETSc /shared/src/PETScNonlinearSolvers.jl:166
│     [27] solve!(x::PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}, nls::PETScNonlinearSolver{typeof(GridapPETSc.snes_from_options)}, op::Gridap.FESpaces.AlgebraicOpFromFEOp)
│        @ Gridap.Algebra ~/.julia/packages/Gridap/rN56R/src/Algebra/NonlinearSolvers.jl:22
│     [28] solve!(u::GridapDistributed.DistributedCellField{MPIArray{Gridap.FESpaces.SingleFieldFEFunction{Gridap.CellData.GenericCellField{ReferenceDomain}}, 1}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, CartesianGrid{2, Float64, typeof(identity)}, Gridap.Arrays.IdentityVector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}, GridapDistributed.DistributedFEFunctionData{PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}}}, solver::Gridap.FESpaces.NonlinearFESolver, feop::Gridap.FESpaces.FEOperatorFromWeakForm, cache::Nothing)
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/FESolvers.jl:163
│     [29] solve!(uh::GridapDistributed.DistributedCellField{MPIArray{Gridap.FESpaces.SingleFieldFEFunction{Gridap.CellData.GenericCellField{ReferenceDomain}}, 1}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, CartesianGrid{2, Float64, typeof(identity)}, Gridap.Arrays.IdentityVector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}, GridapDistributed.DistributedFEFunctionData{PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}}}, solver::Gridap.FESpaces.NonlinearFESolver, op::Gridap.FESpaces.FEOperatorFromWeakForm)
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/FESolvers.jl:14
│     [30] main(distribute::PartitionedArrays.var"#88#89"{MPI.Comm, Bool}, nparts::Tuple{Int64, Int64}, solver::Symbol, strategy::FullyAssembledRows)
│        @ Main /shared/test/PLaplacianTests.jl:111
│     [31] #3
│        @ /shared/test/PLaplacianTests.jl:63 [inlined]
│     [32] with(f::var"#3#4"{PartitionedArrays.var"#88#89"{MPI.Comm, Bool}, Tuple{Int64, Int64}, Symbol}; kwargs::Base.Pairs{Symbol, Vector{SubString{String}}, Tuple{Symbol}, NamedTuple{(:args,), Tuple{Vector{SubString{String}}}}})
│        @ GridapPETSc /shared/src/Environment.jl:38
│     [33] main
│        @ /shared/test/PLaplacianTests.jl:62 [inlined]
│     [34] main
│        @ /shared/test/PLaplacianTests.jl:48 [inlined]
│     [35] #13
│        @ /shared/test/mpi/PLaplacianTests.jl:4 [inlined]
│     [36] with_mpi(f::var"#13#14"; comm::MPI.Comm, duplicate_comm::Bool)
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/mpi_array.jl:73
│     [37] with_mpi(f::Function)
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/mpi_array.jl:64
│     [38] top-level scope
│        @ /shared/test/mpi/PLaplacianTests.jl:3
│     [39] include(mod::Module, _path::String)
│        @ Base ./Base.jl:457
│     [40] exec_options(opts::Base.JLOptions)
│        @ Base ./client.jl:307
│     [41] _start()
│        @ Base ./client.jl:522
└ @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/mpi_array.jl:75
application called MPI_Abort(MPI_COMM_WORLD, 1) - process 0
PLaplacianTests: Error During Test at /shared/test/mpi/runtests.jl:10
  Got exception outside of a @test
  LoadError: failed process: Process(`/root/.julia/artifacts/21f745d9d8c6d3d84dbdaa1ed3ec74b729f1d2b0/bin/mpiexec -n 2 /usr/local/julia/bin/julia -Cnative -J/usr/local/julia/lib/julia/sys.so --depwarn=yes --check-bounds=yes -g1 --color=yes --startup-file=no --project=/shared/test/mpi/../.. /shared/test/mpi/PLaplacianTests.jl`, ProcessExited(1)) [1]
  
  Stacktrace:
    [1] pipeline_error
      @ ./process.jl:565 [inlined]
    [2] run(::Cmd; wait::Bool)
      @ Base ./process.jl:480
    [3] (::Main.GridapPETScTests.GridapPETScMPITests.PLaplacianTestsRun.var"#2#3"{Int64, String, String, String})(cmd::String)
      @ Main.GridapPETScTests.GridapPETScMPITests.PLaplacianTestsRun /shared/test/mpi/mpiexec.jl:0
    [4] (::JLLWrappers.var"#2#3"{Main.GridapPETScTests.GridapPETScMPITests.PLaplacianTestsRun.var"#2#3"{Int64, String, String, String}, String})()
      @ JLLWrappers ~/.julia/packages/JLLWrappers/GfYNv/src/runtime.jl:49
    [5] withenv(::JLLWrappers.var"#2#3"{Main.GridapPETScTests.GridapPETScMPITests.PLaplacianTestsRun.var"#2#3"{Int64, String, String, String}, String}, ::Pair{String, String}, ::Vararg{Pair{String, String}})
      @ Base ./env.jl:197
    [6] withenv_executable_wrapper(f::Function, executable_path::String, PATH::String, LIBPATH::String, adjust_PATH::Bool, adjust_LIBPATH::Bool)
      @ JLLWrappers ~/.julia/packages/JLLWrappers/GfYNv/src/runtime.jl:48
    [7] invokelatest(::Any, ::Any, ::Vararg{Any}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
      @ Base ./essentials.jl:819
    [8] invokelatest(::Any, ::Any, ::Vararg{Any})
      @ Base ./essentials.jl:816
    [9] #mpiexec#3
      @ ~/.julia/packages/JLLWrappers/GfYNv/src/products/executable_generators.jl:28 [inlined]
   [10] mpiexec
      @ ~/.julia/packages/JLLWrappers/GfYNv/src/products/executable_generators.jl:25 [inlined]
   [11] run_mpi_driver(; procs::Int64, file::String)
      @ Main.GridapPETScTests.GridapPETScMPITests.PLaplacianTestsRun /shared/test/mpi/mpiexec.jl:7
   [12] top-level scope
      @ /shared/test/mpi/PLaplacianTestsRun.jl:3
   [13] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [14] include
      @ /shared/test/mpi/runtests.jl:1 [inlined]
   [15] macro expansion
      @ /shared/test/mpi/runtests.jl:10 [inlined]
   [16] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [17] macro expansion
      @ /shared/test/mpi/runtests.jl:10 [inlined]
   [18] top-level scope
      @ ./timing.jl:273 [inlined]
   [19] top-level scope
      @ /shared/test/mpi/runtests.jl:0
   [20] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [21] include
      @ /shared/test/runtests.jl:1 [inlined]
   [22] macro expansion
      @ /shared/test/runtests.jl:7 [inlined]
   [23] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [24] macro expansion
      @ /shared/test/runtests.jl:7 [inlined]
   [25] top-level scope
      @ ./timing.jl:273 [inlined]
   [26] top-level scope
      @ /shared/test/runtests.jl:0
   [27] include(fname::String)
      @ Base.MainInclude ./client.jl:478
   [28] top-level scope
      @ none:6
   [29] eval
      @ ./boot.jl:370 [inlined]
   [30] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:280
   [31] _start()
      @ Base ./client.jl:522
  in expression starting at /shared/test/mpi/PLaplacianTestsRun.jl:1
 22.466360 seconds (815.07 k allocations: 56.011 MiB, 0.61% gc time, 2.99% compilation time)
WARNING! There are options you set that were not used!
WARNING! could be spelling mistake, etc!
There are 9 unused database options. They are:
Option left: name:-ksp_type value: gmres source: command line
Option left: name:-pc_type value: jacobi source: command line
Option left: name:-snes_atol value: 0.0 source: command line
Option left: name:-snes_converged_reason (no value) source: command line
Option left: name:-snes_linesearch_damping value: 1.0 source: command line
Option left: name:-snes_linesearch_type value: basic source: command line
Option left: name:-snes_monitor (no value) source: command line
Option left: name:-snes_rtol value: 1.0e-14 source: command line
Option left: name:-snes_type value: newtonls source: command line
┌ Error: 
│   exception =
│    User-defined reduction operators are currently not supported on non-Intel architectures.
│    See https://github.com/JuliaParallel/MPI.jl/issues/404 for more details.
│    
│    You may want to use `@RegisterOp` to statically register `f`.
│    
│    Stacktrace:
│      [1] error(s::String)
│        @ Base ./error.jl:35
│      [2] MPI.Op(f::Function, T::Type; iscommutative::Bool)
│        @ MPI ~/.julia/packages/MPI/TKXAj/src/operators.jl:109
│      [3] MPI.Op(f::Function, T::Type)
│        @ MPI ~/.julia/packages/MPI/TKXAj/src/operators.jl:102
│      [4] reduction!(op::PartitionedArrays.var"#and#50", b::MPIArray{Bool, 1}, a::MPIArray{Bool, 1}; destination::Symbol, init::Bool)
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/mpi_array.jl:426
│      [5] reduction(op::Function, a::MPIArray{Bool, 1}; kwargs::Base.Pairs{Symbol, Any, Tuple{Symbol, Symbol}, NamedTuple{(:destination, :init), Tuple{Symbol, Bool}}})
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:517
│      [6] (::PartitionedArrays.var"#is_included#47")(snd_ids_a::MPIArray{Vector{Int32}, 1}, snd_ids_b::MPIArray{Vector{Int32}, 1})
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:606
│      [7] ExchangeGraph_impl_with_neighbors(snd_ids::MPIArray{Vector{Int32}, 1}, neighbors::ExchangeGraph{MPIArray{Vector{Int32}, 1}})
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:612
│      [8] #ExchangeGraph#39
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:592 [inlined]
│      [9] ExchangeGraph
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:585 [inlined]
│     [10] #compute_assembly_neighbors#136
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/p_range.jl:411 [inlined]
│     [11] compute_assembly_neighbors
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/p_range.jl:399 [inlined]
│     [12] assembly_neighbors(indices::MPIArray{OwnAndGhostIndices{Nothing}, 1}; kwargs::Base.Pairs{Symbol, ExchangeGraph{MPIArray{Vector{Int32}, 1}}, Tuple{Symbol}, NamedTuple{(:neighbors,), Tuple{ExchangeGraph{MPIArray{Vector{Int32}, 1}}}}})
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/p_range.jl:386
│     [13] assembly_neighbors
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/p_range.jl:380 [inlined]
│     [14] _find_neighbours!
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:964 [inlined]
│     [15] #_setup_prange_impl_#178
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1249 [inlined]
│     [16] _setup_prange_impl_(ngdofs::Int64, dofs_gids_partition::MPIArray{LocalIndices, 1}, gids_ghost_to_global::MPIArray{Vector{Int64}, 1}, gids_ghost_to_owner::MPIArray{Vector{Int32}, 1})
│        @ GridapDistributed ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1235
│     [17] _setup_prange_with_ghosts(dofs_gids_prange::PRange{MPIArray{LocalIndices, 1}}, gids::MPIArray{Vector{Int64}, 1})
│        @ GridapDistributed ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1197
│     [18] #_setup_prange#165
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1135 [inlined]
│     [19] _setup_prange
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1131 [inlined]
│     [20] _fa_create_from_nz_with_callback
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:559 [inlined]
│     [21] create_from_nz(a::GridapDistributed.DistributedAllocationCOO{FullyAssembledRows, MPIArray{Gridap.Algebra.AllocationCOO{SparseMatrixCSR{0, Float64, Int64}, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}}, Vector{Int64}, Vector{Float64}}, 1}, PRange{MPIArray{LocalIndices, 1}}, PRange{MPIArray{LocalIndices, 1}}}, c_fespace::GridapDistributed.PVectorAllocationTrackOnlyValues{FullyAssembledRows, MPIArray{Vector{Float64}, 1}, PRange{MPIArray{LocalIndices, 1}}})
│        @ GridapDistributed ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:763
│     [22] assemble_matrix_and_vector(a::GridapDistributed.DistributedSparseMatrixAssembler{FullyAssembledRows, MPIArray{Gridap.FESpaces.GenericSparseMatrixAssembler, 1}, GridapDistributed.PSparseMatrixBuilderCOO{SparseMatrixCSR{0, Float64, Int64}, FullyAssembledRows}, GridapDistributed.PVectorBuilder{Vector{Float64}, FullyAssembledRows}, PRange{MPIArray{LocalIndices, 1}}, PRange{MPIArray{LocalIndices, 1}}}, data::MPIArray{Tuple{Tuple{Vector{Any}, Vector{Any}, Vector{Any}}, Tuple{Vector{Any}, Vector{Any}, Vector{Any}}, Tuple{Vector{Any}, Vector{Any}}}, 1})
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/SparseMatrixAssemblers.jl:102
│     [23] residual_and_jacobian(op::Gridap.FESpaces.FEOperatorFromWeakForm, uh::GridapDistributed.DistributedCellField{MPIArray{Gridap.FESpaces.SingleFieldFEFunction{Gridap.CellData.GenericCellField{ReferenceDomain}}, 1}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, CartesianGrid{2, Float64, typeof(identity)}, Gridap.Arrays.IdentityVector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}, GridapDistributed.DistributedFEFunctionData{PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}}})
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/FEOperatorsFromWeakForm.jl:101
│     [24] residual_and_jacobian(op::Gridap.FESpaces.AlgebraicOpFromFEOp, x::PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64})
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/FEOperators.jl:194
│     [25] _setup_cache(x::PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}, nls::PETScNonlinearSolver{typeof(GridapPETSc.snes_from_options)}, op::Gridap.FESpaces.AlgebraicOpFromFEOp)
│        @ GridapPETSc /shared/src/PETScNonlinearSolvers.jl:127
│     [26] solve!(x::PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}, nls::PETScNonlinearSolver{typeof(GridapPETSc.snes_from_options)}, op::Gridap.FESpaces.AlgebraicOpFromFEOp, #unused#::Nothing)
│        @ GridapPETSc /shared/src/PETScNonlinearSolvers.jl:166
│     [27] solve!(x::PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}, nls::PETScNonlinearSolver{typeof(GridapPETSc.snes_from_options)}, op::Gridap.FESpaces.AlgebraicOpFromFEOp)
│        @ Gridap.Algebra ~/.julia/packages/Gridap/rN56R/src/Algebra/NonlinearSolvers.jl:22
│     [28] solve!(u::GridapDistributed.DistributedCellField{MPIArray{Gridap.FESpaces.SingleFieldFEFunction{Gridap.CellData.GenericCellField{ReferenceDomain}}, 1}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, CartesianGrid{2, Float64, typeof(identity)}, Gridap.Arrays.IdentityVector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}, GridapDistributed.DistributedFEFunctionData{PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}}}, solver::Gridap.FESpaces.NonlinearFESolver, feop::Gridap.FESpaces.FEOperatorFromWeakForm, cache::Nothing)
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/FESolvers.jl:163
│     [29] solve!(uh::GridapDistributed.DistributedCellField{MPIArray{Gridap.FESpaces.SingleFieldFEFunction{Gridap.CellData.GenericCellField{ReferenceDomain}}, 1}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, CartesianGrid{2, Float64, typeof(identity)}, Gridap.Arrays.IdentityVector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}, GridapDistributed.DistributedFEFunctionData{PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}}}, solver::Gridap.FESpaces.NonlinearFESolver, op::Gridap.FESpaces.FEOperatorFromWeakForm)
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/FESolvers.jl:14
│     [30] main(distribute::PartitionedArrays.var"#88#89"{MPI.Comm, Bool}, nparts::Tuple{Int64, Int64}, solver::Symbol, strategy::FullyAssembledRows)
│        @ Main /shared/test/PLaplacianTests.jl:111
│     [31] #3
│        @ /shared/test/PLaplacianTests.jl:63 [inlined]
│     [32] with(f::var"#3#4"{PartitionedArrays.var"#88#89"{MPI.Comm, Bool}, Tuple{Int64, Int64}, Symbol}; kwargs::Base.Pairs{Symbol, Vector{SubString{String}}, Tuple{Symbol}, NamedTuple{(:args,), Tuple{Vector{SubString{String}}}}})
│        @ GridapPETSc /shared/src/Environment.jl:38
│     [33] main
│        @ /shared/test/PLaplacianTests.jl:62 [inlined]
│     [34] main
│        @ /shared/test/PLaplacianTests.jl:48 [inlined]
│     [35] #15
│        @ /shared/test/mpi/GCTests.jl:38 [inlined]
│     [36] with_mpi(f::var"#15#16"; comm::MPI.Comm, duplicate_comm::Bool)
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/mpi_array.jl:73
│     [37] with_mpi(f::Function)
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/mpi_array.jl:64
│     [38] top-level scope
│        @ /shared/test/mpi/GCTests.jl:37
│     [39] include(mod::Module, _path::String)
│        @ Base ./Base.jl:457
│     [40] exec_options(opts::Base.JLOptions)
│        @ Base ./client.jl:307
│     [41] _start()
│        @ Base ./client.jl:522
└ @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/mpi_array.jl:75
application called MPI_Abort(MPI_COMM_WORLD, 1) - process 2
GCTests: Error During Test at /shared/test/mpi/runtests.jl:11
  Got exception outside of a @test
  LoadError: failed process: Process(`/root/.julia/artifacts/21f745d9d8c6d3d84dbdaa1ed3ec74b729f1d2b0/bin/mpiexec -n 4 /usr/local/julia/bin/julia -Cnative -J/usr/local/julia/lib/julia/sys.so --depwarn=yes --check-bounds=yes -g1 --color=yes --startup-file=no --project=/shared/test/mpi/../.. /shared/test/mpi/GCTests.jl`, ProcessExited(1)) [1]
  
  Stacktrace:
    [1] pipeline_error
      @ ./process.jl:565 [inlined]
    [2] run(::Cmd; wait::Bool)
      @ Base ./process.jl:480
    [3] (::Main.GridapPETScTests.GridapPETScMPITests.GCTestsRun.var"#2#3"{Int64, String, String, String})(cmd::String)
      @ Main.GridapPETScTests.GridapPETScMPITests.GCTestsRun /shared/test/mpi/mpiexec.jl:0
    [4] (::JLLWrappers.var"#2#3"{Main.GridapPETScTests.GridapPETScMPITests.GCTestsRun.var"#2#3"{Int64, String, String, String}, String})()
      @ JLLWrappers ~/.julia/packages/JLLWrappers/GfYNv/src/runtime.jl:49
    [5] withenv(::JLLWrappers.var"#2#3"{Main.GridapPETScTests.GridapPETScMPITests.GCTestsRun.var"#2#3"{Int64, String, String, String}, String}, ::Pair{String, String}, ::Vararg{Pair{String, String}})
      @ Base ./env.jl:197
    [6] withenv_executable_wrapper(f::Function, executable_path::String, PATH::String, LIBPATH::String, adjust_PATH::Bool, adjust_LIBPATH::Bool)
      @ JLLWrappers ~/.julia/packages/JLLWrappers/GfYNv/src/runtime.jl:48
    [7] invokelatest(::Any, ::Any, ::Vararg{Any}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
      @ Base ./essentials.jl:819
    [8] invokelatest(::Any, ::Any, ::Vararg{Any})
      @ Base ./essentials.jl:816
    [9] #mpiexec#3
      @ ~/.julia/packages/JLLWrappers/GfYNv/src/products/executable_generators.jl:28 [inlined]
   [10] mpiexec
      @ ~/.julia/packages/JLLWrappers/GfYNv/src/products/executable_generators.jl:25 [inlined]
   [11] run_mpi_driver(; procs::Int64, file::String)
      @ Main.GridapPETScTests.GridapPETScMPITests.GCTestsRun /shared/test/mpi/mpiexec.jl:7
   [12] top-level scope
      @ /shared/test/mpi/GCTestsRun.jl:3
   [13] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [14] include
      @ /shared/test/mpi/runtests.jl:1 [inlined]
   [15] macro expansion
      @ /shared/test/mpi/runtests.jl:11 [inlined]
   [16] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [17] macro expansion
      @ /shared/test/mpi/runtests.jl:11 [inlined]
   [18] top-level scope
      @ ./timing.jl:273 [inlined]
   [19] top-level scope
      @ /shared/test/mpi/runtests.jl:0
   [20] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [21] include
      @ /shared/test/runtests.jl:1 [inlined]
   [22] macro expansion
      @ /shared/test/runtests.jl:7 [inlined]
   [23] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [24] macro expansion
      @ /shared/test/runtests.jl:7 [inlined]
   [25] top-level scope
      @ ./timing.jl:273 [inlined]
   [26] top-level scope
      @ /shared/test/runtests.jl:0
   [27] include(fname::String)
      @ Base.MainInclude ./client.jl:478
   [28] top-level scope
      @ none:6
   [29] eval
      @ ./boot.jl:370 [inlined]
   [30] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:280
   [31] _start()
      @ Base ./client.jl:522
  in expression starting at /shared/test/mpi/GCTestsRun.jl:1
 23.106745 seconds (48.59 k allocations: 3.332 MiB, 0.13% compilation time)
┌ Error: 
│   exception =
│    User-defined reduction operators are currently not supported on non-Intel architectures.
│    See https://github.com/JuliaParallel/MPI.jl/issues/404 for more details.
│    
│    You may want to use `@RegisterOp` to statically register `f`.
│    
│    Stacktrace:
│      [1] error(s::String)
│        @ Base ./error.jl:35
│      [2] MPI.Op(f::Function, T::Type; iscommutative::Bool)
│        @ MPI ~/.julia/packages/MPI/TKXAj/src/operators.jl:109
│      [3] MPI.Op(f::Function, T::Type)
│        @ MPI ~/.julia/packages/MPI/TKXAj/src/operators.jl:102
│      [4] reduction!(op::PartitionedArrays.var"#and#50", b::MPIArray{Bool, 1}, a::MPIArray{Bool, 1}; destination::Symbol, init::Bool)
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/mpi_array.jl:426
│      [5] reduction(op::Function, a::MPIArray{Bool, 1}; kwargs::Base.Pairs{Symbol, Any, Tuple{Symbol, Symbol}, NamedTuple{(:destination, :init), Tuple{Symbol, Bool}}})
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:517
│      [6] (::PartitionedArrays.var"#is_included#47")(snd_ids_a::MPIArray{Vector{Int32}, 1}, snd_ids_b::MPIArray{Vector{Int32}, 1})
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:606
│      [7] ExchangeGraph_impl_with_neighbors(snd_ids::MPIArray{Vector{Int32}, 1}, neighbors::ExchangeGraph{MPIArray{Vector{Int32}, 1}})
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:612
│      [8] #ExchangeGraph#39
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:592 [inlined]
│      [9] ExchangeGraph
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/primitives.jl:585 [inlined]
│     [10] #compute_assembly_neighbors#136
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/p_range.jl:411 [inlined]
│     [11] compute_assembly_neighbors
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/p_range.jl:399 [inlined]
│     [12] assembly_neighbors(indices::MPIArray{OwnAndGhostIndices{Nothing}, 1}; kwargs::Base.Pairs{Symbol, ExchangeGraph{MPIArray{Vector{Int32}, 1}}, Tuple{Symbol}, NamedTuple{(:neighbors,), Tuple{ExchangeGraph{MPIArray{Vector{Int32}, 1}}}}})
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/p_range.jl:386
│     [13] assembly_neighbors
│        @ ~/.julia/packages/PartitionedArrays/py6uo/src/p_range.jl:380 [inlined]
│     [14] _find_neighbours!
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:964 [inlined]
│     [15] #_setup_prange_impl_#178
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1249 [inlined]
│     [16] _setup_prange_impl_(ngdofs::Int64, dofs_gids_partition::MPIArray{LocalIndices, 1}, gids_ghost_to_global::MPIArray{Vector{Int64}, 1}, gids_ghost_to_owner::MPIArray{Vector{Int32}, 1})
│        @ GridapDistributed ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1235
│     [17] _setup_prange_with_ghosts(dofs_gids_prange::PRange{MPIArray{LocalIndices, 1}}, gids::MPIArray{Vector{Int64}, 1})
│        @ GridapDistributed ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1197
│     [18] #_setup_prange#165
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1135 [inlined]
│     [19] _setup_prange
│        @ ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:1131 [inlined]
│     [20] _sa_create_from_nz_with_callback(callback::GridapDistributed.var"#callback#122", async_callback::GridapDistributed.var"#async_callback#123", a::GridapDistributed.DistributedAllocationCOO{SubAssembledRows, MPIArray{Gridap.Algebra.AllocationCOO{SparseMatrixCSR{0, Float64, Int64}, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}}, Vector{Int64}, Vector{Float64}}, 1}, PRange{MPIArray{LocalIndices, 1}}, PRange{MPIArray{LocalIndices, 1}}}, b::GridapDistributed.PVectorAllocationTrackTouchedAndValues{MPIArray{GridapDistributed.ArrayAllocationTrackTouchedAndValues{Vector{Float64}}, 1}, MPIArray{Vector{Float64}, 1}, PRange{MPIArray{LocalIndices, 1}}})
│        @ GridapDistributed ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:599
│     [21] create_from_nz(a::GridapDistributed.DistributedAllocationCOO{SubAssembledRows, MPIArray{Gridap.Algebra.AllocationCOO{SparseMatrixCSR{0, Float64, Int64}, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}}, Vector{Int64}, Vector{Float64}}, 1}, PRange{MPIArray{LocalIndices, 1}}, PRange{MPIArray{LocalIndices, 1}}}, b::GridapDistributed.PVectorAllocationTrackTouchedAndValues{MPIArray{GridapDistributed.ArrayAllocationTrackTouchedAndValues{Vector{Float64}}, 1}, MPIArray{Vector{Float64}, 1}, PRange{MPIArray{LocalIndices, 1}}})
│        @ GridapDistributed ~/.julia/packages/GridapDistributed/HsRvz/src/Algebra.jl:786
│     [22] assemble_matrix_and_vector(a::GridapDistributed.DistributedSparseMatrixAssembler{SubAssembledRows, MPIArray{GenericSparseMatrixAssembler, 1}, GridapDistributed.PSparseMatrixBuilderCOO{SparseMatrixCSR{0, Float64, Int64}, SubAssembledRows}, GridapDistributed.PVectorBuilder{Vector{Float64}, SubAssembledRows}, PRange{MPIArray{LocalIndices, 1}}, PRange{MPIArray{LocalIndices, 1}}}, data::MPIArray{Tuple{Tuple{Vector{Any}, Vector{Any}, Vector{Any}}, Tuple{Vector{Any}, Vector{Any}, Vector{Any}}, Tuple{Vector{Any}, Vector{Any}}}, 1})
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/SparseMatrixAssemblers.jl:102
│     [23] AffineFEOperator(weakform::Gridap.FESpaces.var"#75#76"{var"#a#9"{GridapDistributed.DistributedMeasure{MPIArray{Gridap.CellData.GenericMeasure, 1}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, Gridap.Geometry.GridView{2, 2, CartesianGrid{2, Float64, typeof(identity)}, Vector{Int64}}, Gridap.Arrays.LazyArray{FillArrays.Fill{Reindex{Gridap.Arrays.IdentityVector{Int64}}, 1, Tuple{Base.OneTo{Int64}}}, Int64, 1, Tuple{Vector{Int64}}}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}}}, var"#l#10"{GridapDistributed.DistributedMeasure{MPIArray{Gridap.CellData.GenericMeasure, 1}, GridapDistributed.DistributedTriangulation{1, 2, MPIArray{Gridap.Geometry.TriangulationView{1, 2, BoundaryTriangulation{1, 2, Gridap.Geometry.BodyFittedTriangulation{1, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, Gridap.Geometry.GridView{1, 2, Gridap.Geometry.UnstructuredGrid{1, 2, Float64, Gridap.Geometry.NonOriented, Nothing}, Vector{Int64}}, Vector{Int64}}, Gridap.Geometry.FaceToCellGlue{Vector{Int64}, Gridap.Arrays.LazyArray{FillArrays.Fill{Reindex{Vector{Int8}}, 1, Tuple{Base.OneTo{Int64}}}, Int8, 1, Tuple{Vector{Int64}}}, FillArrays.Fill{Int8, 1, Tuple{Base.OneTo{Int64}}}, Vector{Vector{Int8}}}}, Vector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}}, GridapDistributed.DistributedMeasure{MPIArray{Gridap.CellData.GenericMeasure, 1}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, Gridap.Geometry.GridView{2, 2, CartesianGrid{2, Float64, typeof(identity)}, Vector{Int64}}, Gridap.Arrays.LazyArray{FillArrays.Fill{Reindex{Gridap.Arrays.IdentityVector{Int64}}, 1, Tuple{Base.OneTo{Int64}}}, Int64, 1, Tuple{Vector{Int64}}}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}}, GridapDistributed.DistributedCellField{MPIArray{Gridap.CellData.OperationCellField{ReferenceDomain}, 1}, GridapDistributed.DistributedTriangulation{1, 2, MPIArray{Gridap.Geometry.TriangulationView{1, 2, BoundaryTriangulation{1, 2, Gridap.Geometry.BodyFittedTriangulation{1, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, Gridap.Geometry.GridView{1, 2, Gridap.Geometry.UnstructuredGrid{1, 2, Float64, Gridap.Geometry.NonOriented, Nothing}, Vector{Int64}}, Vector{Int64}}, Gridap.Geometry.FaceToCellGlue{Vector{Int64}, Gridap.Arrays.LazyArray{FillArrays.Fill{Reindex{Vector{Int8}}, 1, Tuple{Base.OneTo{Int64}}}, Int8, 1, Tuple{Vector{Int64}}}, FillArrays.Fill{Int8, 1, Tuple{Base.OneTo{Int64}}}, Vector{Vector{Int8}}}}, Vector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}, Nothing}, var"#f#8"{var"#u#7"{Int64}}}}, trial::GridapDistributed.DistributedSingleFieldFESpace{MPIArray{TrialFESpace{UnconstrainedFESpace{Vector{Float64}, CellConformity{FillArrays.Fill{Int64, 1, Tuple{Base.OneTo{Int64}}}}}}, 1}, PRange{MPIArray{LocalIndices, 1}}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, CartesianGrid{2, Float64, typeof(identity)}, Gridap.Arrays.IdentityVector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}, PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}, Nothing}, test::GridapDistributed.DistributedSingleFieldFESpace{MPIArray{UnconstrainedFESpace{Vector{Float64}, CellConformity{FillArrays.Fill{Int64, 1, Tuple{Base.OneTo{Int64}}}}}, 1}, PRange{MPIArray{LocalIndices, 1}}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, CartesianGrid{2, Float64, typeof(identity)}, Gridap.Arrays.IdentityVector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}, PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}, Nothing}, assem::GridapDistributed.DistributedSparseMatrixAssembler{SubAssembledRows, MPIArray{GenericSparseMatrixAssembler, 1}, GridapDistributed.PSparseMatrixBuilderCOO{SparseMatrixCSR{0, Float64, Int64}, SubAssembledRows}, GridapDistributed.PVectorBuilder{Vector{Float64}, SubAssembledRows}, PRange{MPIArray{LocalIndices, 1}}, PRange{MPIArray{LocalIndices, 1}}})
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/AffineFEOperators.jl:38
│     [24] AffineFEOperator(::var"#a#9"{GridapDistributed.DistributedMeasure{MPIArray{Gridap.CellData.GenericMeasure, 1}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, Gridap.Geometry.GridView{2, 2, CartesianGrid{2, Float64, typeof(identity)}, Vector{Int64}}, Gridap.Arrays.LazyArray{FillArrays.Fill{Reindex{Gridap.Arrays.IdentityVector{Int64}}, 1, Tuple{Base.OneTo{Int64}}}, Int64, 1, Tuple{Vector{Int64}}}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}}}, ::var"#l#10"{GridapDistributed.DistributedMeasure{MPIArray{Gridap.CellData.GenericMeasure, 1}, GridapDistributed.DistributedTriangulation{1, 2, MPIArray{Gridap.Geometry.TriangulationView{1, 2, BoundaryTriangulation{1, 2, Gridap.Geometry.BodyFittedTriangulation{1, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, Gridap.Geometry.GridView{1, 2, Gridap.Geometry.UnstructuredGrid{1, 2, Float64, Gridap.Geometry.NonOriented, Nothing}, Vector{Int64}}, Vector{Int64}}, Gridap.Geometry.FaceToCellGlue{Vector{Int64}, Gridap.Arrays.LazyArray{FillArrays.Fill{Reindex{Vector{Int8}}, 1, Tuple{Base.OneTo{Int64}}}, Int8, 1, Tuple{Vector{Int64}}}, FillArrays.Fill{Int8, 1, Tuple{Base.OneTo{Int64}}}, Vector{Vector{Int8}}}}, Vector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}}, GridapDistributed.DistributedMeasure{MPIArray{Gridap.CellData.GenericMeasure, 1}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, Gridap.Geometry.GridView{2, 2, CartesianGrid{2, Float64, typeof(identity)}, Vector{Int64}}, Gridap.Arrays.LazyArray{FillArrays.Fill{Reindex{Gridap.Arrays.IdentityVector{Int64}}, 1, Tuple{Base.OneTo{Int64}}}, Int64, 1, Tuple{Vector{Int64}}}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}}, GridapDistributed.DistributedCellField{MPIArray{Gridap.CellData.OperationCellField{ReferenceDomain}, 1}, GridapDistributed.DistributedTriangulation{1, 2, MPIArray{Gridap.Geometry.TriangulationView{1, 2, BoundaryTriangulation{1, 2, Gridap.Geometry.BodyFittedTriangulation{1, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, Gridap.Geometry.GridView{1, 2, Gridap.Geometry.UnstructuredGrid{1, 2, Float64, Gridap.Geometry.NonOriented, Nothing}, Vector{Int64}}, Vector{Int64}}, Gridap.Geometry.FaceToCellGlue{Vector{Int64}, Gridap.Arrays.LazyArray{FillArrays.Fill{Reindex{Vector{Int8}}, 1, Tuple{Base.OneTo{Int64}}}, Int8, 1, Tuple{Vector{Int64}}}, FillArrays.Fill{Int8, 1, Tuple{Base.OneTo{Int64}}}, Vector{Vector{Int8}}}}, Vector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}, Nothing}, var"#f#8"{var"#u#7"{Int64}}}, ::GridapDistributed.DistributedSingleFieldFESpace{MPIArray{TrialFESpace{UnconstrainedFESpace{Vector{Float64}, CellConformity{FillArrays.Fill{Int64, 1, Tuple{Base.OneTo{Int64}}}}}}, 1}, PRange{MPIArray{LocalIndices, 1}}, GridapDistributed.DistributedTriangulation{2, 2, MPIArray{Gridap.Geometry.BodyFittedTriangulation{2, 2, CartesianDiscreteModel{2, Float64, typeof(identity)}, CartesianGrid{2, Float64, typeof(identity)}, Gridap.Arrays.IdentityVector{Int64}}, 1}, GridapDistributed.GenericDistributedDiscreteModel{2, 2, MPIArray{CartesianDiscreteModel{2, Float64, typeof(identity)}, 1}, Vector{PRange}, GridapDistributed.DistributedCartesianDescriptor{MPIArray{Int64, 1}, Tuple{Int64, Int64}, Gridap.Geometry.CartesianDescriptor{2, Float64, typeof(identity)}}}}, PVector{Vector{Float64}, MPIArray{Vector{Float64}, 1}, MPIArray{LocalIndices, 1}, MPIArray{PartitionedArrays.VectorAssemblyCache{Float64}, 1}, Float64}, Nothing}, ::Vararg{Any})
│        @ Gridap.FESpaces ~/.julia/packages/Gridap/rN56R/src/FESpaces/AffineFEOperators.jl:51
│     [25] (::var"#3#6"{Tuple{Int64, Int64}, Symbol, MPIArray{Int64, 1}})()
│        @ Main /shared/test/PoissonTests.jl:77
│     [26] #with#2
│        @ /shared/src/Environment.jl:38 [inlined]
│     [27] with
│        @ /shared/src/Environment.jl:36 [inlined]
│     [28] main(distribute::PartitionedArrays.var"#88#89"{MPI.Comm, Bool}, nparts::Tuple{Int64, Int64}, solver::Symbol)
│        @ Main /shared/test/PoissonTests.jl:46
│     [29] main(distribute::Function, nparts::Tuple{Int64, Int64})
│        @ Main /shared/test/PoissonTests.jl:30
│     [30] (::var"#13#14")(distribute::Function)
│        @ Main /shared/test/mpi/PoissonTests.jl:4
│     [31] with_mpi(f::var"#13#14"; comm::MPI.Comm, duplicate_comm::Bool)
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/mpi_array.jl:73
│     [32] with_mpi(f::Function)
│        @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/mpi_array.jl:64
│     [33] top-level scope
│        @ /shared/test/mpi/PoissonTests.jl:3
│     [34] include(mod::Module, _path::String)
│        @ Base ./Base.jl:457
│     [35] exec_options(opts::Base.JLOptions)
│        @ Base ./client.jl:307
│     [36] _start()
│        @ Base ./client.jl:522
└ @ PartitionedArrays ~/.julia/packages/PartitionedArrays/py6uo/src/mpi_array.jl:75
application called MPI_Abort(MPI_COMM_WORLD, 1) - process 0
PoissonTests: Error During Test at /shared/test/mpi/runtests.jl:12
  Got exception outside of a @test
  LoadError: failed process: Process(`/root/.julia/artifacts/21f745d9d8c6d3d84dbdaa1ed3ec74b729f1d2b0/bin/mpiexec -n 4 /usr/local/julia/bin/julia -Cnative -J/usr/local/julia/lib/julia/sys.so --depwarn=yes --check-bounds=yes -g1 --color=yes --startup-file=no --project=/shared/test/mpi/../.. /shared/test/mpi/PoissonTests.jl`, ProcessExited(1)) [1]
  
  Stacktrace:
    [1] pipeline_error
      @ ./process.jl:565 [inlined]
    [2] run(::Cmd; wait::Bool)
      @ Base ./process.jl:480
    [3] (::Main.GridapPETScTests.GridapPETScMPITests.PoissonTestsRun.var"#2#3"{Int64, String, String, String})(cmd::String)
      @ Main.GridapPETScTests.GridapPETScMPITests.PoissonTestsRun /shared/test/mpi/mpiexec.jl:0
    [4] (::JLLWrappers.var"#2#3"{Main.GridapPETScTests.GridapPETScMPITests.PoissonTestsRun.var"#2#3"{Int64, String, String, String}, String})()
      @ JLLWrappers ~/.julia/packages/JLLWrappers/GfYNv/src/runtime.jl:49
    [5] withenv(::JLLWrappers.var"#2#3"{Main.GridapPETScTests.GridapPETScMPITests.PoissonTestsRun.var"#2#3"{Int64, String, String, String}, String}, ::Pair{String, String}, ::Vararg{Pair{String, String}})
      @ Base ./env.jl:197
    [6] withenv_executable_wrapper(f::Function, executable_path::String, PATH::String, LIBPATH::String, adjust_PATH::Bool, adjust_LIBPATH::Bool)
      @ JLLWrappers ~/.julia/packages/JLLWrappers/GfYNv/src/runtime.jl:48
    [7] invokelatest(::Any, ::Any, ::Vararg{Any}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
      @ Base ./essentials.jl:819
    [8] invokelatest(::Any, ::Any, ::Vararg{Any})
      @ Base ./essentials.jl:816
    [9] #mpiexec#3
      @ ~/.julia/packages/JLLWrappers/GfYNv/src/products/executable_generators.jl:28 [inlined]
   [10] mpiexec
      @ ~/.julia/packages/JLLWrappers/GfYNv/src/products/executable_generators.jl:25 [inlined]
   [11] run_mpi_driver(; procs::Int64, file::String)
      @ Main.GridapPETScTests.GridapPETScMPITests.PoissonTestsRun /shared/test/mpi/mpiexec.jl:7
   [12] top-level scope
      @ /shared/test/mpi/PoissonTestsRun.jl:3
   [13] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [14] include
      @ /shared/test/mpi/runtests.jl:1 [inlined]
   [15] macro expansion
      @ /shared/test/mpi/runtests.jl:12 [inlined]
   [16] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [17] macro expansion
      @ /shared/test/mpi/runtests.jl:12 [inlined]
   [18] top-level scope
      @ ./timing.jl:273 [inlined]
   [19] top-level scope
      @ /shared/test/mpi/runtests.jl:0
   [20] include(mod::Module, _path::String)
      @ Base ./Base.jl:457
   [21] include
      @ /shared/test/runtests.jl:1 [inlined]
   [22] macro expansion
      @ /shared/test/runtests.jl:7 [inlined]
   [23] macro expansion
      @ /usr/local/julia/share/julia/stdlib/v1.9/Test/src/Test.jl:1498 [inlined]
   [24] macro expansion
      @ /shared/test/runtests.jl:7 [inlined]
   [25] top-level scope
      @ ./timing.jl:273 [inlined]
   [26] top-level scope
      @ /shared/test/runtests.jl:0
   [27] include(fname::String)
      @ Base.MainInclude ./client.jl:478
   [28] top-level scope
      @ none:6
   [29] eval
      @ ./boot.jl:370 [inlined]
   [30] exec_options(opts::Base.JLOptions)
      @ Base ./client.jl:280
   [31] _start()
      @ Base ./client.jl:522
  in expression starting at /shared/test/mpi/PoissonTestsRun.jl:1
 31.086707 seconds (48.59 k allocations: 3.335 MiB, 0.19% compilation time)
[ Info: Skipping DarcyTests since petsc is not configured with mumps.
[ Info: Skipping DarcyTests since petsc is not configured with mumps.
[ Info: Skipping DarcyTests since petsc is not configured with mumps.
[ Info: Skipping DarcyTests since petsc is not configured with mumps.
  2.900624 seconds (40.37 k allocations: 2.749 MiB, 2.30% compilation time)
Test Summary:       | Pass  Error  Total     Time
MPI                 |    2      3      5  1m29.4s
  PartitionedArrays |    1             1     9.6s
  PLaplacianTests   |           1      1    22.5s
  GCTests           |           1      1    23.1s
  PoissonTests      |           1      1    31.1s
  DarcyTests        |    1             1     2.9s
ERROR: LoadError: Some tests did not pass: 2 passed, 0 failed, 3 errored, 0 broken.
in expression starting at /shared/test/runtests.jl:1
ERROR: Package GridapPETSc errored during testing

[JordiManyer]

That seems to be a MAC-specific thing from PETSc, right?

[lamBOOO]

According to the error, yes. 🤔

│    User-defined reduction operators are currently not supported on non-Intel architectures.
│    See https://github.com/JuliaParallel/MPI.jl/issues/404 for more details.
│    
│    You may want to use `@RegisterOp` to statically register `f`.

[ericneiva]

Hi, just popping in to say that I observed a similar error with a different MPI application in Gridap. I was using the Windows Subsystem for Linux 2 on an ARM architecture.

As implied in the issue referred to in the error, this is Julia not yet providing complete support to some platform + architecture combos (often ARM). https://julialang.org/downloads/#supported_platforms

@lamBOOO maybe some search through Julia discourse and GH issues will let you know if there is an easy workaround for your particular platform+architecture combo or any plans to fully support it in the near future. Hope this helps.

[lamBOOO]

Hi @ericneiva @JordiManyer, I looked into this macOS issue and it seems to be related to custom MPI reduction and ARM CPUs within the PartitionedArrays package. I opened an issue there with some proposal to fix it (PartitionedArrays/PartitionedArrays.jl#208).

[lamBOOO]

The above-mentioned PR landed in the meantime, so PartionedArrays doesn’t raise an error on macOS anymore.

@JordiManyer, you told me in Milano that GridapPETSc is behind PartionedArrays. What needs to be done to upgrade, and can I help somehow?

[JordiManyer]

Hi @lamBOOO , thank you for the PR in PA.jl. Yes, we are currently limited to v0.3.4. I have a PR open in GridapDistributed to update compatibilities, but I can only dedicate so much time.

My honest opinion is that this is probably above what anyone except for me and Alberto can do, it requires very deep knowledge of GridapDistributed. And the upgrade is no joke, as you might see in the PR. I have it 90% there, but there are some issues still.

[lamBOOO]

Ahh okay, thanks, I didn't search in GD.jl and found it now (gridap/GridapDistributed.jl#157). I'm not sure if and how I can help but at least I know now where to start 👍

[fverdugo]

Hi @lamBOOO @JordiManyer it is also possible to add a commit in PA after the last in version 0.3.x as a workaround.