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CuArray(sol) scalar-indexes GPU arrays for SecondOrderODEProblem (ArrayPartition) solutions

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#662 0 comentarios 0 reacciones 0 asignados Ver en GitHub

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Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
45/100
Tipo de issue
Error
Claridad
Bien especificado
Estado de actividad
Activo
Stack tecnológico
julia
Área
backend

Línea de trabajo

The issue is in the CuArray constructor for solutions of SecondOrderODEProblem where states are ArrayPartitions of CuArrays. Start by examining the CuArray constructor in RecursiveArrayTools.jl and how it handles AbstractVectorOfArray with ArrayPartition elements. The failing test is in test/GPU/ode_gpu.jl; run it to see the scalar indexing error. Look at the difference between ODEProblem and SecondOrderODEProblem solutions. The fix must avoid scalar indexing while preserving allowscalar(false).

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

CuArray(sol) for the solution of a SecondOrderODEProblem on CUDA arrays scalar-indexes the GPU arrays and errors under the default allowscalar(false). The solution's states are ArrayPartitions of CuArrays. The plain ODEProblem case (Array(sol) with CuArray states) works.

test/GPU/ode_gpu.jl was written for this (https://discourse.julialang.org/t/results-of-secondorderodeproblem-give-error-this-object-is-not-a-gpu-array/82100), but no test group ever included it. https://github.com/SciML/RecursiveArrayTools.jl/pull/659 wires it into the GPU group, and the self-hosted GPU job fails there: https://github.com/SciML/RecursiveArrayTools.jl/actions/runs/35874813098/job/107236637535

using CUDA, LinearAlgebra, OrdinaryDiffEq, Test
u0 = cu(rand(100)); du0 = cu(rand(100)); A = cu(randn(100, 100))
f(ddu, du, u, p, t) = mul!(ddu, A, u)
sol = solve(SecondOrderODEProblem(f, du0, u0, (0.0f0, 1.0f0)), Tsit5())
@test SciMLBase.successful_retcode(sol)   # passes
CuArray(sol)                               # errors
Expression: size(CuArray(sol), 1) == 200
Scalar indexing is disallowed.
Invocation of getindex resulted in scalar indexing of a GPU array.

The failing versions are those resolved by that CI job: CUDA 6.4, OrdinaryDiffEq 7.8.1, RecursiveArrayTools master (4.5.2). Julia 1 is on the self-hosted GPU runner. I have not reproduced it locally because this machine has no GPU. A CPU substitute with JLArrays and allowscalar(false) did not reproduce it for JLArray(sol), so the scalar path may be specific to the CuArray constructor on AbstractVectorOfArray{<:Any,<:Any,<:ArrayPartition}.

#659 stays open as the regression test for this. Its test must not be weakened to make it pass.

🤖 Filed by Claude Code 2.1.280 (model claude-opus-5-5[1m]) from the qa-hygiene goal cycle.

https://claude.ai/code/session_01QgnmpexRwud38wrs3XvBfV

Lenguaje dominante
Julia
Estrellas
233
Forks
76
Merge medio
5 h 33 min
PR fusionados (30 d)
11

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