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exponential!() broken for CuSparseMatrixCSC #181

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mcarmesin opened this issue Nov 11, 2024 · 3 comments
Open

exponential!() broken for CuSparseMatrixCSC #181

mcarmesin opened this issue Nov 11, 2024 · 3 comments
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@mcarmesin
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Describe the bug 🐞

Calculating the matrix exponential of a CUDA sparse matrix fails with trowing the exception
ArgumentError: Attempt to use a freed reference.
or
Error: Scalar Indexing is disallowed
when selecting ExpMethodGeneric()

Expected behavior

Calculation of the matrix exponential like exp(A)

Minimal Reproducible Example 👇

using ExponentialUtilities
using CUDA
using SparseArrays

A = cu(sprand(50,50,.01))

exponential!(A)
exponential!(A, ExpMethodGeneric())

Error & Stacktrace ⚠️

ERROR: ArgumentError: Attempt to use a freed reference.
Stacktrace:
[1] getindex
    @ ~/.julia/packages/GPUArrays/qt4ax/src/host/abstractarray.jl:70 [inlined]
  [2] unsafe_convert
    @ ~/.julia/packages/CUDA/2kjXI/src/array.jl:434 [inlined]
  [3] unsafe_convert(::Type{CuPtr{Nothing}}, a::CuArray{Int32, 1, CUDA.DeviceMemory})
    @ CUDA ~/.julia/packages/CUDA/2kjXI/src/pointer.jl:62
  [4] macro expansion
    @ ~/.julia/packages/CUDA/2kjXI/lib/utils/call.jl:211 [inlined]
  [5] macro expansion
    @ ~/.julia/packages/CUDA/2kjXI/lib/cusparse/libcusparse.jl:5274 [inlined]
  [6] #728
    @ ~/.julia/packages/CUDA/2kjXI/lib/utils/call.jl:35 [inlined]
  [7] retry_reclaim(f::CUDA.CUSPARSE.var"#728#729"{…}, retry_if::CUDA.CUSPARSE.var"#retry_if#1")
    @ CUDA ~/.julia/packages/CUDA/2kjXI/src/memory.jl:434
  [8] check
    @ ~/.julia/packages/CUDA/2kjXI/lib/cusparse/libcusparse.jl:24 [inlined]
  [9] cusparseCreateCsr
    @ ~/.julia/packages/CUDA/2kjXI/lib/utils/call.jl:34 [inlined]
 [10] CUDA.CUSPARSE.CuSparseMatrixDescriptor(A::CUDA.CUSPARSE.CuSparseMatrixCSR{…}, IndexBase::Char; transposed::Bool)
    @ CUDA.CUSPARSE ~/.julia/packages/CUDA/2kjXI/lib/cusparse/helpers.jl:189
 [11] CuSparseMatrixDescriptor
    @ ~/.julia/packages/CUDA/2kjXI/lib/cusparse/helpers.jl:179 [inlined]
 [12] gemm!(transa::Char, transb::Char, alpha::Bool, A::CUDA.CUSPARSE.CuSparseMatrixCSR{…}, B::CUDA.CUSPARSE.CuSparseMatrixCSR{…}, beta::Bool, C::CUDA.CUSPARSE.CuSparseMatrixCSR{…}, index::Char, algo::CUDA.CUSPARSE.cusparseSpGEMMAlg_t)
    @ CUDA.CUSPARSE ~/.julia/packages/CUDA/2kjXI/lib/cusparse/generic.jl:412
 [13] gemm!
    @ ~/.julia/packages/CUDA/2kjXI/lib/cusparse/generic.jl:490 [inlined]
 [14] gemm!
    @ ~/.julia/packages/CUDA/2kjXI/lib/cusparse/generic.jl:487 [inlined]
 [15] generic_matmatmul!(C::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, tA::Char, tB::Char, A::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, B::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, alpha::Bool, beta::Bool)
    @ CUDA.CUSPARSE ~/.julia/packages/CUDA/2kjXI/lib/cusparse/interfaces.jl:167
 [16] generic_matmatmul!
    @ ~/.julia/packages/CUDA/2kjXI/lib/cusparse/interfaces.jl:157 [inlined]
 [17] mul!
    @ /lustre/home/software/bwhpc/common/math/julia/1.10.5/share/julia/stdlib/v1.10/LinearAlgebra/src/matmul.jl:263 [inlined]
 [18] mul!
    @ /lustre/home/software/bwhpc/common/math/julia/1.10.5/share/julia/stdlib/v1.10/LinearAlgebra/src/matmul.jl:237 [inlined]
 [19] exp_gen!(cache::Vector{…}, A::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, ::Val{…})
    @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_generated/exp_4.jl:21
 [20] exponential!(A::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, method::ExpMethodHigham2005, _cache::Tuple{…})
    @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_noalloc.jl:101
 [21] exponential!
    @ ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_noalloc.jl:83 [inlined]
 [22] exponential!(A::CUDA.CUSPARSE.CuSparseMatrixCSC{Float32, Int32})
    @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp.jl:15
 [23] top-level scope
    @ ~/CN/test_cu_sparse_exponentiation.jl:7
Some type information was truncated. Use `show(err)` to see complete types.[1] getindex
    @ ~/.julia/packages/GPUArrays/qt4ax/src/host/abstractarray.jl:70 [inlined]
  [2] unsafe_convert
    @ ~/.julia/packages/CUDA/2kjXI/src/array.jl:434 [inlined]
  [3] unsafe_convert(::Type{CuPtr{Nothing}}, a::CuArray{Int32, 1, CUDA.DeviceMemory})
    @ CUDA ~/.julia/packages/CUDA/2kjXI/src/pointer.jl:62
  [4] macro expansion
    @ ~/.julia/packages/CUDA/2kjXI/lib/utils/call.jl:211 [inlined]
  [5] macro expansion
    @ ~/.julia/packages/CUDA/2kjXI/lib/cusparse/libcusparse.jl:5274 [inlined]
  [6] #728
    @ ~/.julia/packages/CUDA/2kjXI/lib/utils/call.jl:35 [inlined]
  [7] retry_reclaim(f::CUDA.CUSPARSE.var"#728#729"{…}, retry_if::CUDA.CUSPARSE.var"#retry_if#1")
    @ CUDA ~/.julia/packages/CUDA/2kjXI/src/memory.jl:434
  [8] check
    @ ~/.julia/packages/CUDA/2kjXI/lib/cusparse/libcusparse.jl:24 [inlined]
  [9] cusparseCreateCsr
    @ ~/.julia/packages/CUDA/2kjXI/lib/utils/call.jl:34 [inlined]
 [10] CUDA.CUSPARSE.CuSparseMatrixDescriptor(A::CUDA.CUSPARSE.CuSparseMatrixCSR{…}, IndexBase::Char; transposed::Bool)
    @ CUDA.CUSPARSE ~/.julia/packages/CUDA/2kjXI/lib/cusparse/helpers.jl:189
 [11] CuSparseMatrixDescriptor
    @ ~/.julia/packages/CUDA/2kjXI/lib/cusparse/helpers.jl:179 [inlined]
 [12] gemm!(transa::Char, transb::Char, alpha::Bool, A::CUDA.CUSPARSE.CuSparseMatrixCSR{…}, B::CUDA.CUSPARSE.CuSparseMatrixCSR{…}, beta::Bool, C::CUDA.CUSPARSE.CuSparseMatrixCSR{…}, index::Char, algo::CUDA.CUSPARSE.cusparseSpGEMMAlg_t)
    @ CUDA.CUSPARSE ~/.julia/packages/CUDA/2kjXI/lib/cusparse/generic.jl:412
 [13] gemm!
    @ ~/.julia/packages/CUDA/2kjXI/lib/cusparse/generic.jl:490 [inlined]
 [14] gemm!
    @ ~/.julia/packages/CUDA/2kjXI/lib/cusparse/generic.jl:487 [inlined]
 [15] generic_matmatmul!(C::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, tA::Char, tB::Char, A::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, B::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, alpha::Bool, beta::Bool)
    @ CUDA.CUSPARSE ~/.julia/packages/CUDA/2kjXI/lib/cusparse/interfaces.jl:167
 [16] generic_matmatmul!
    @ ~/.julia/packages/CUDA/2kjXI/lib/cusparse/interfaces.jl:157 [inlined]
 [17] mul!
    @ /lustre/home/software/bwhpc/common/math/julia/1.10.5/share/julia/stdlib/v1.10/LinearAlgebra/src/matmul.jl:263 [inlined]
 [18] mul!
    @ /lustre/home/software/bwhpc/common/math/julia/1.10.5/share/julia/stdlib/v1.10/LinearAlgebra/src/matmul.jl:237 [inlined]
 [19] exp_gen!(cache::Vector{…}, A::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, ::Val{…})
    @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_generated/exp_4.jl:21
 [20] exponential!(A::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, method::ExpMethodHigham2005, _cache::Tuple{…})
    @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_noalloc.jl:101
 [21] exponential!
    @ ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_noalloc.jl:83 [inlined]
 [22] exponential!(A::CUDA.CUSPARSE.CuSparseMatrixCSC{Float32, Int32})
    @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp.jl:15
 [23] top-level scope
    @ ~/CN/test_cu_sparse_exponentiation.jl:7
Some type information was truncated. Use `show(err)` to see complete types.

ERROR: Scalar indexing is disallowed.
Invocation of getindex resulted in scalar indexing of a GPU array.
This is typically caused by calling an iterating implementation of a method.
Such implementations *do not* execute on the GPU, but very slowly on the CPU,
and therefore should be avoided.

If you want to allow scalar iteration, use `allowscalar` or `@allowscalar`
to enable scalar iteration globally or for the operations in question.
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:35
  [2] errorscalar(op::String)
    @ GPUArraysCore ~/.julia/packages/GPUArraysCore/GMsgk/src/GPUArraysCore.jl:155
  [3] _assertscalar(op::String, behavior::GPUArraysCore.ScalarIndexing)
    @ GPUArraysCore ~/.julia/packages/GPUArraysCore/GMsgk/src/GPUArraysCore.jl:128
  [4] assertscalar(op::String)
    @ GPUArraysCore ~/.julia/packages/GPUArraysCore/GMsgk/src/GPUArraysCore.jl:116
  [5] getindex(A::CuArray{Int32, 1, CUDA.DeviceMemory}, I::Int64)
    @ GPUArrays ~/.julia/packages/GPUArrays/qt4ax/src/host/indexing.jl:50
  [6] getindex(A::CUDA.CUSPARSE.CuSparseMatrixCSC{Float64, Int32}, i0::Int64, i1::Int64)
    @ CUDA.CUSPARSE ~/.julia/packages/CUDA/2kjXI/lib/cusparse/array.jl:387
  [7] _getindex
    @ ./abstractarray.jl:1341 [inlined]
  [8] getindex
    @ ./abstractarray.jl:1291 [inlined]
  [9] exp_generic_core!(y1::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, y2::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, y3::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, x::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, ::Val{…})
    @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_generic.jl:192
 [10] exp_generic!(y1::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, y2::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, y3::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, x::CUDA.CUSPARSE.CuSparseMatrixCSC{…}, s::Int64, ::Val{…})
    @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_generic.jl:170
 [11] exp_generic_mutable
    @ ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_generic.jl:166 [inlined]
 [12] exponential!(x::CUDA.CUSPARSE.CuSparseMatrixCSC{Float32, Int32}, method::ExpMethodGeneric{Val{13}()}, cache::Nothing)
    @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_generic.jl:136
 [13] exponential!(x::CUDA.CUSPARSE.CuSparseMatrixCSC{Float32, Int32}, method::ExpMethodGeneric{Val{13}()})
    @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_generic.jl:128
 [14] top-level scope
    @ ~/CN/test_cu_sparse_exponentiation.jl:9
Some type information was truncated. Use `show(err)` to see complete types.

Environment (please complete the following information):

  • Output of using Pkg; Pkg.status()
 [47edcb42] ADTypes v1.9.0
  [79e6a3ab] Adapt v4.1.1
  [7d9fca2a] Arpack v0.5.4
  [6e4b80f9] BenchmarkTools v1.5.0
  [052768ef] CUDA v5.5.2
  [071ae1c0] DiffEqGPU v3.4.1
⌃ [0c46a032] DifferentialEquations v7.13.0
  [5b8099bc] DomainSets v0.7.14
  [d4d017d3] ExponentialUtilities v1.26.1
⌃ [f6369f11] ForwardDiff v0.10.37
⌅ [46192b85] GPUArraysCore v0.1.6
  [40713840] IncompleteLU v0.2.1
  [7a12625a] LinearMaps v3.11.3
  [7ed4a6bd] LinearSolve v2.36.2
  [94925ecb] MethodOfLines v0.11.6
⌃ [961ee093] ModelingToolkit v9.49.0
⌃ [1dea7af3] OrdinaryDiffEq v6.80.1
  [94395366] ParallelStencil v0.13.6
  [f0f68f2c] PlotlyJS v0.18.15
  [91a5bcdd] Plots v1.40.8
  [33c8b6b6] ProgressLogging v0.1.4
  [295af30f] Revise v3.6.2
⌃ [0bca4576] SciMLBase v2.58.1
  [c0aeaf25] SciMLOperators v0.3.12
  [05bca326] SimpleDiffEq v1.11.1
  [ce78b400] SimpleUnPack v1.1.0
  [9f842d2f] SparseConnectivityTracer v0.6.8
⌃ [0c5d862f] Symbolics v6.17.0
  [2f01184e] SparseArrays v1.10.0
  • Output of using Pkg; Pkg.status(; mode = PKGMODE_MANIFEST)
[47edcb42] ADTypes v1.9.0
  [621f4979] AbstractFFTs v1.5.0
  [1520ce14] AbstractTrees v0.4.5
  [7d9f7c33] Accessors v0.1.38
  [79e6a3ab] Adapt v4.1.1
  [66dad0bd] AliasTables v1.1.3
  [ec485272] ArnoldiMethod v0.4.0
  [7d9fca2a] Arpack v0.5.4
⌃ [4fba245c] ArrayInterface v7.16.0
  [4c555306] ArrayLayouts v1.10.4
  [bf4720bc] AssetRegistry v0.1.0
  [a9b6321e] Atomix v0.1.0
  [13072b0f] AxisAlgorithms v1.1.0
  [ab4f0b2a] BFloat16s v0.5.0
  [aae01518] BandedMatrices v1.7.5
  [6e4b80f9] BenchmarkTools v1.5.0
  [e2ed5e7c] Bijections v0.1.9
  [d1d4a3ce] BitFlags v0.1.9
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [ad839575] Blink v0.12.9
  [8e7c35d0] BlockArrays v1.1.1
⌃ [764a87c0] BoundaryValueDiffEq v5.9.1
  [fa961155] CEnum v0.5.0
  [2a0fbf3d] CPUSummary v0.2.6
  [00ebfdb7] CSTParser v3.4.3
  [052768ef] CUDA v5.5.2
  [1af6417a] CUDA_Runtime_Discovery v0.3.5
⌅ [d35fcfd7] CellArrays v0.2.2
  [d360d2e6] ChainRulesCore v1.25.0
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [da1fd8a2] CodeTracking v1.3.6
  [944b1d66] CodecZlib v0.7.6
⌃ [35d6a980] ColorSchemes v3.27.0
⌅ [3da002f7] ColorTypes v0.11.5
⌅ [c3611d14] ColorVectorSpace v0.10.0
⌅ [5ae59095] Colors v0.12.11
  [861a8166] Combinatorics v1.0.2
  [a80b9123] CommonMark v0.8.15
  [38540f10] CommonSolve v0.2.4
  [bbf7d656] CommonSubexpressions v0.3.1
  [f70d9fcc] CommonWorldInvalidations v1.0.0
  [34da2185] Compat v4.16.0
  [b152e2b5] CompositeTypes v0.1.4
  [a33af91c] CompositionsBase v0.1.2
  [2569d6c7] ConcreteStructs v0.2.3
  [f0e56b4a] ConcurrentUtilities v2.4.2
  [187b0558] ConstructionBase v1.5.8
  [d38c429a] Contour v0.6.3
  [adafc99b] CpuId v0.3.1
  [a8cc5b0e] Crayons v4.1.1
  [9a962f9c] DataAPI v1.16.0
  [a93c6f00] DataFrames v1.7.0
  [864edb3b] DataStructures v0.18.20
  [e2d170a0] DataValueInterfaces v1.0.0
  [bcd4f6db] DelayDiffEq v5.48.1
  [8bb1440f] DelimitedFiles v1.9.1
  [2b5f629d] DiffEqBase v6.158.3
⌅ [459566f4] DiffEqCallbacks v3.8.0
  [071ae1c0] DiffEqGPU v3.4.1
  [77a26b50] DiffEqNoiseProcess v5.23.0
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
⌃ [0c46a032] DifferentialEquations v7.13.0
⌃ [a0c0ee7d] DifferentiationInterface v0.6.18
  [8d63f2c5] DispatchDoctor v0.4.17
  [b4f34e82] Distances v0.10.12
⌃ [31c24e10] Distributions v0.25.112
  [ffbed154] DocStringExtensions v0.9.3
  [5b8099bc] DomainSets v0.7.14
  [7c1d4256] DynamicPolynomials v0.6.0
⌃ [06fc5a27] DynamicQuantities v1.2.0
  [4e289a0a] EnumX v1.0.4
  [f151be2c] EnzymeCore v0.8.5
  [460bff9d] ExceptionUnwrapping v0.1.10
  [d4d017d3] ExponentialUtilities v1.26.1
  [e2ba6199] ExprTools v0.1.10
⌅ [6b7a57c9] Expronicon v0.8.5
  [c87230d0] FFMPEG v0.4.2
  [9d29842c] FastAlmostBandedMatrices v0.1.4
  [7034ab61] FastBroadcast v0.3.5
  [9aa1b823] FastClosures v0.3.2
  [29a986be] FastLapackInterface v2.0.4
  [1a297f60] FillArrays v1.13.0
  [64ca27bc] FindFirstFunctions v1.4.1
  [6a86dc24] FiniteDiff v2.26.0
  [53c48c17] FixedPointNumbers v0.8.5
  [1fa38f19] Format v1.3.7
⌃ [f6369f11] ForwardDiff v0.10.37
  [069b7b12] FunctionWrappers v1.1.3
  [77dc65aa] FunctionWrappersWrappers v0.1.3
  [de31a74c] FunctionalCollections v0.5.0
⌅ [d9f16b24] Functors v0.4.12
⌅ [0c68f7d7] GPUArrays v10.3.1
⌅ [46192b85] GPUArraysCore v0.1.6
⌅ [61eb1bfa] GPUCompiler v0.27.8
  [28b8d3ca] GR v0.73.8
  [c145ed77] GenericSchur v0.5.4
  [c27321d9] Glob v1.3.1
  [86223c79] Graphs v1.12.0
  [42e2da0e] Grisu v1.0.2
⌃ [cd3eb016] HTTP v1.10.9
  [9fb69e20] Hiccup v0.2.2
  [3e5b6fbb] HostCPUFeatures v0.1.17
⌃ [34004b35] HypergeometricFunctions v0.3.24
  [615f187c] IfElse v0.1.1
  [40713840] IncompleteLU v0.2.1
  [d25df0c9] Inflate v0.1.5
  [842dd82b] InlineStrings v1.4.2
  [18e54dd8] IntegerMathUtils v0.1.2
  [a98d9a8b] Interpolations v0.15.1
  [8197267c] IntervalSets v0.7.10
  [3587e190] InverseFunctions v0.1.17
  [41ab1584] InvertedIndices v1.3.0
  [92d709cd] IrrationalConstants v0.2.2
  [82899510] IteratorInterfaceExtensions v1.0.0
  [1019f520] JLFzf v0.1.8
  [692b3bcd] JLLWrappers v1.6.1
  [97c1335a] JSExpr v0.5.4
  [682c06a0] JSON v0.21.4
  [98e50ef6] JuliaFormatter v1.0.62
  [aa1ae85d] JuliaInterpreter v0.9.36
  [ccbc3e58] JumpProcesses v9.14.0
  [ef3ab10e] KLU v0.6.0
  [63c18a36] KernelAbstractions v0.9.29
  [ba0b0d4f] Krylov v0.9.8
  [929cbde3] LLVM v9.1.3
  [8b046642] LLVMLoopInfo v1.0.0
  [b964fa9f] LaTeXStrings v1.4.0
  [23fbe1c1] Latexify v0.16.5
  [10f19ff3] LayoutPointers v0.1.17
  [50d2b5c4] Lazy v0.15.1
  [5078a376] LazyArrays v2.2.1
  [2d8b4e74] LevyArea v1.0.0
  [87fe0de2] LineSearch v0.1.4
  [d3d80556] LineSearches v7.3.0
  [7a12625a] LinearMaps v3.11.3
  [7ed4a6bd] LinearSolve v2.36.2
  [2ab3a3ac] LogExpFunctions v0.3.28
  [e6f89c97] LoggingExtras v1.1.0
  [bdcacae8] LoopVectorization v0.12.171
  [6f1432cf] LoweredCodeUtils v3.0.5
  [d8e11817] MLStyle v0.4.17
  [1914dd2f] MacroTools v0.5.13
  [d125e4d3] ManualMemory v0.1.8
  [a3b82374] MatrixFactorizations v3.0.1
  [bb5d69b7] MaybeInplace v0.1.4
  [739be429] MbedTLS v1.1.9
  [442fdcdd] Measures v0.3.2
  [94925ecb] MethodOfLines v0.11.6
  [e1d29d7a] Missings v1.2.0
⌃ [961ee093] ModelingToolkit v9.49.0
  [46d2c3a1] MuladdMacro v0.2.4
  [102ac46a] MultivariatePolynomials v0.5.7
  [ffc61752] Mustache v1.0.20
  [d8a4904e] MutableArithmetics v1.5.2
  [a975b10e] Mux v1.0.2
  [d41bc354] NLSolversBase v7.8.3
  [2774e3e8] NLsolve v4.5.1
  [5da4648a] NVTX v0.3.4
  [77ba4419] NaNMath v1.0.2
⌅ [8913a72c] NonlinearSolve v3.15.1
  [510215fc] Observables v0.5.5
  [6fe1bfb0] OffsetArrays v1.14.1
  [4d8831e6] OpenSSL v1.4.3
  [429524aa] Optim v1.9.4
  [bac558e1] OrderedCollections v1.6.3
⌃ [1dea7af3] OrdinaryDiffEq v6.80.1
⌃ [a7812802] PDEBase v0.1.15
  [90014a1f] PDMats v0.11.31
  [65ce6f38] PackageExtensionCompat v1.0.2
  [94395366] ParallelStencil v0.13.6
  [d96e819e] Parameters v0.12.3
  [69de0a69] Parsers v2.8.1
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  • Output of versioninfo()
Julia Version 1.10.5
Commit 6f3fdf7b362 (2024-08-27 14:19 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 96 × Intel(R) Xeon(R) Gold 6252 CPU @ 2.10GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, cascadelake)
Threads: 48 default, 0 interactive, 24 GC (on 96 virtual cores)
@mcarmesin mcarmesin added the bug Something isn't working label Nov 11, 2024
@ChrisRackauckas
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I'm not 100% sure what the behavior you'd want here is. The matrix exponential of a sparse matrix is dense unless the matrix is diagonal. Diagonal GPU matrices would use Diagonal{CuArray}, so that wouldn't be this type. Which means that the result here is almost certainly dense. Should this just dispatch to exp(CuArray(A))? It seems having the user actually have to request that isn't the worst thing as a somewhat safety measure, since generally asking for a densifying operation on a sparse matrix is a bad idea.

What the user would almost certainly want to do instead here is exp(At)*v operations, which can be done sparsely. My understanding is that as long as A*v is supported in the array type, which it is here, then it should just work. So then erroring and having people use expv and phiv is the better option.

@mcarmesin
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I agree that densifying would be not a good solution for various reasons. Probably it would be best, to have exponential!() undefined for sparse matrices, like the base exp!(). Btw. exponential!() is also broken for SparseMatrixCSC():

ERROR: pointer_from_objref cannot be used on immutable objects
Stacktrace:
 [1] error(s::String)
   @ Base ./error.jl:35
 [2] pointer_from_objref
   @ ./pointer.jl:269 [inlined]
 [3] ldiv_for_generated!(C::SparseMatrixCSC{…}, A::SparseMatrixCSC{…}, B::SparseMatrixCSC{…})
   @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_noalloc.jl:32
 [4] exp_gen!(cache::Vector{SparseMatrixCSC{Float64, Int64}}, A::SparseMatrixCSC{Float64, Int64}, ::Val{4})
   @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_generated/exp_4.jl:63
 [5] exponential!(A::SparseMatrixCSC{Float64, Int64}, method::ExpMethodHigham2005, _cache::Tuple{Vector{…}, SparseVector{…}})
   @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_noalloc.jl:101
 [6] exponential!(A::SparseMatrixCSC{Float64, Int64}, method::ExpMethodHigham2005)
   @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp_noalloc.jl:83
 [7] exponential!(A::SparseMatrixCSC{Float64, Int64})
   @ ExponentialUtilities ~/.julia/packages/ExponentialUtilities/xLH9y/src/exp.jl:15
 [8] top-level scope
   @ ~/CN/test_cu_sparse_exponentiation.jl:10

@mcarmesin mcarmesin mentioned this issue Nov 12, 2024
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@ChrisRackauckas
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Btw. exponential!() is also broken for SparseMatrixCSC():

Yeah we should probably just throw an error on <: AbstractSparseMatrix saying

exp(A) on a sparse matrix is generally dense. This operation is not allowed with exponential. If you wished to compute exp(At)*v, see expv. Otherwise to override this error, densify the matrix before calling, i.e. exponential(Matrix(A))

@mcarmesin mcarmesin mentioned this issue Nov 14, 2024
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