Batch solve failed for problems with decreasing intervals

**Describe the bug 🐞**

When I trying to solve in backward direction I always get a *batch solve failed* with collapsed bounds of `tspan` (e.g. if I set up `tspan = (-1.0, -3.0)` it will show that `tspan` is `-1.0f0` and `ts = [-1.0, -1.0]`). I've tried to use either positive or negative values of `dt`, several kernels (GPUTsit5, GPUVern9, etc).

**Expected behavior**

The negative `tspan` direction should work the same way as positive.

**Minimal Reproducible Example 👇**

I've found problem on another system, but for MRE I reproduce it with lorenz equation, and got the same behavior.

```julia
using DiffEqGPU, OrdinaryDiffEq, StaticArrays, CUDA

function lorenz(u, p, t)
    σ = p[1]
    ρ = p[2]
    β = p[3]
    du1 = σ * (u[2] - u[1])
    du2 = u[1] * (ρ - u[3]) - u[2]
    du3 = u[1] * u[2] - β * u[3]
    return SVector{3}(du1, du2, du3)
end

FloatType = Float32

u0 = @SVector FloatType[1.0; 0.0; 0.0]

tspan = (FloatType(0.0), -FloatType(10.0))
p = @SVector FloatType[10.0, 28.0, 8 / 3.0]
prob = ODEProblem{false}(lorenz, u0, tspan, p)
prob_func = (prob, i, repeat) -> remake(prob, p = (@SVector rand(FloatType, 3)) .* p)
monteprob = EnsembleProblem(prob, prob_func = prob_func, safetycopy = false)

sol = solve(
    monteprob, 
    GPUTsit5(), 
    EnsembleGPUKernel(CUDA.CUDABackend()), 
    trajectories = 10, 
    dt = -1e-4,
)
```

**Error & Stacktrace ⚠️**

```julia
Batch solve failed
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:35
  [2] #112
    @ ~/.julia/packages/DiffEqGPU/0Jmg9/src/solve.jl:181 [inlined]
  [3] (::DiffEqGPU.var"#112#128"{SciMLBase.EnsembleProblem{SciMLBase.ODEProblem{StaticArraysCore.SVector{3, Float32}, Tuple{Float32, Float32}, false, StaticArraysCore.SVector{3, Float32}, SciMLBase.ODEFunction{false, SciMLBase.AutoSpecialize, typeof(Main.var"workspace#2".lorenz), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, var"#27#28"{typeof(SciMLBase.remake), StaticArraysCore.SVector{3, Float32}, DataType, typeof(*)}, typeof(SciMLBase.DEFAULT_OUTPUT_FUNC), typeof(SciMLBase.DEFAULT_REDUCTION), Nothing}, DiffEqGPU.GPUTsit5, Matrix{Float32}})(i::Int64)
    @ DiffEqGPU ./none:0
  [4] iterate
    @ ./generator.jl:48 [inlined]
  [5] collect(itr::Base.Generator{Base.OneTo{Int64}, DiffEqGPU.var"#112#128"{SciMLBase.EnsembleProblem{SciMLBase.ODEProblem{StaticArraysCore.SVector{3, Float32}, Tuple{Float32, Float32}, false, StaticArraysCore.SVector{3, Float32}, SciMLBase.ODEFunction{false, SciMLBase.AutoSpecialize, typeof(Main.var"workspace#2".lorenz), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, var"#27#28"{typeof(SciMLBase.remake), StaticArraysCore.SVector{3, Float32}, DataType, typeof(*)}, typeof(SciMLBase.DEFAULT_OUTPUT_FUNC), typeof(SciMLBase.DEFAULT_REDUCTION), Nothing}, DiffEqGPU.GPUTsit5, Matrix{Float32}}})
    @ Base ./array.jl:791
  [6] batch_solve(ensembleprob::SciMLBase.EnsembleProblem{SciMLBase.ODEProblem{StaticArraysCore.SVector{3, Float32}, Tuple{Float32, Float32}, false, StaticArraysCore.SVector{3, Float32}, SciMLBase.ODEFunction{false, SciMLBase.AutoSpecialize, typeof(Main.var"workspace#2".lorenz), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, var"#27#28"{typeof(SciMLBase.remake), StaticArraysCore.SVector{3, Float32}, DataType, typeof(*)}, typeof(SciMLBase.DEFAULT_OUTPUT_FUNC), typeof(SciMLBase.DEFAULT_REDUCTION), Nothing}, alg::DiffEqGPU.GPUTsit5, ensemblealg::DiffEqGPU.EnsembleGPUKernel{CUDA.CUDAKernels.CUDABackend}, I::UnitRange{Int64}, adaptive::Bool; kwargs::@Kwargs{unstable_check::DiffEqGPU.var"#100#106", dt::Float64})
    @ DiffEqGPU ~/.julia/packages/DiffEqGPU/0Jmg9/src/solve.jl:175
  [7] macro expansion
    @ ./timing.jl:421 [inlined]
  [8] __solve(ensembleprob::SciMLBase.EnsembleProblem{SciMLBase.ODEProblem{StaticArraysCore.SVector{3, Float32}, Tuple{Float32, Float32}, false, StaticArraysCore.SVector{3, Float32}, SciMLBase.ODEFunction{false, SciMLBase.AutoSpecialize, typeof(Main.var"workspace#2".lorenz), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, var"#27#28"{typeof(SciMLBase.remake), StaticArraysCore.SVector{3, Float32}, DataType, typeof(*)}, typeof(SciMLBase.DEFAULT_OUTPUT_FUNC), typeof(SciMLBase.DEFAULT_REDUCTION), Nothing}, alg::DiffEqGPU.GPUTsit5, ensemblealg::DiffEqGPU.EnsembleGPUKernel{CUDA.CUDAKernels.CUDABackend}; trajectories::Int64, batch_size::Int64, unstable_check::Function, adaptive::Bool, kwargs::@Kwargs{dt::Float64})
    @ DiffEqGPU ~/.julia/packages/DiffEqGPU/0Jmg9/src/solve.jl:55
  [9] solve(::SciMLBase.EnsembleProblem{SciMLBase.ODEProblem{StaticArraysCore.SVector{3, Float32}, Tuple{Float32, Float32}, false, StaticArraysCore.SVector{3, Float32}, SciMLBase.ODEFunction{false, SciMLBase.AutoSpecialize, typeof(Main.var"workspace#2".lorenz), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, var"#27#28"{typeof(SciMLBase.remake), StaticArraysCore.SVector{3, Float32}, DataType, typeof(*)}, typeof(SciMLBase.DEFAULT_OUTPUT_FUNC), typeof(SciMLBase.DEFAULT_REDUCTION), Nothing}, ::DiffEqGPU.GPUTsit5, ::Vararg{Any}; kwargs::@Kwargs{trajectories::Int64, dt::Float64})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/qvEPa/src/solve.jl:1221
 [10] solve
    @ ~/.julia/packages/DiffEqBase/qvEPa/src/solve.jl:1218 [inlined]
 [11] ##function_wrapped_cell#823
    @ ~/.julia/pluto_notebooks/Tiny magic.jl#==#42d6c72a-62d0-4f32-9b32-c373ccda448d:1 [inlined]
```

**Environment (please complete the following information):**

  - Output of `using Pkg; Pkg.status()`

```julia
Status `/tmp/jl_t6MjG8/Project.toml`
  [052768ef] CUDA v5.8.2
  [071ae1c0] DiffEqGPU v3.7.0
  [1dea7af3] OrdinaryDiffEq v6.98.0
  [90137ffa] StaticArrays v1.9.13
  [44cfe95a] Pkg v1.11.0
```

  - Output of `using Pkg; Pkg.status(; mode = PKGMODE_MANIFEST)`

```julia
Status `/tmp/jl_t6MjG8/Manifest.toml`
  [47edcb42] ADTypes v1.15.0
  [621f4979] AbstractFFTs v1.5.0
  [7d9f7c33] Accessors v0.1.42
  [79e6a3ab] Adapt v4.3.0
  [4fba245c] ArrayInterface v7.19.0
  [4c555306] ArrayLayouts v1.11.1
  [a9b6321e] Atomix v1.1.1
  [ab4f0b2a] BFloat16s v0.5.1
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [70df07ce] BracketingNonlinearSolve v1.3.0
  [fa961155] CEnum v0.5.0
  [2a0fbf3d] CPUSummary v0.2.6
  [052768ef] CUDA v5.8.2
  [1af6417a] CUDA_Runtime_Discovery v0.3.5
  [d360d2e6] ChainRulesCore v1.25.2
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [3da002f7] ColorTypes v0.12.1
  [5ae59095] Colors v0.13.1
  [38540f10] CommonSolve v0.2.4
  [bbf7d656] CommonSubexpressions v0.3.1
  [f70d9fcc] CommonWorldInvalidations v1.0.0
  [34da2185] Compat v4.16.0
  [a33af91c] CompositionsBase v0.1.2
  [2569d6c7] ConcreteStructs v0.2.3
  [187b0558] ConstructionBase v1.6.0
  [adafc99b] CpuId v0.3.1
  [a8cc5b0e] Crayons v4.1.1
  [9a962f9c] DataAPI v1.16.0
  [a93c6f00] DataFrames v1.7.0
  [864edb3b] DataStructures v0.18.22
  [e2d170a0] DataValueInterfaces v1.0.0
  [2b5f629d] DiffEqBase v6.176.0
  [071ae1c0] DiffEqGPU v3.7.0
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [a0c0ee7d] DifferentiationInterface v0.7.1
  [ffbed154] DocStringExtensions v0.9.5
  [4e289a0a] EnumX v1.0.5
  [f151be2c] EnzymeCore v0.8.12
  [d4d017d3] ExponentialUtilities v1.27.0
  [e2ba6199] ExprTools v0.1.10
  [55351af7] ExproniconLite v0.10.14
  [7034ab61] FastBroadcast v0.3.5
  [9aa1b823] FastClosures v0.3.2
  [442a2c76] FastGaussQuadrature v1.0.2
  [a4df4552] FastPower v1.1.3
  [1a297f60] FillArrays v1.13.0
  [6a86dc24] FiniteDiff v2.27.0
  [53c48c17] FixedPointNumbers v0.8.5
  [f6369f11] ForwardDiff v1.0.1
  [069b7b12] FunctionWrappers v1.1.3
  [77dc65aa] FunctionWrappersWrappers v0.1.3
  [0c68f7d7] GPUArrays v11.2.3
  [46192b85] GPUArraysCore v0.2.0
  [61eb1bfa] GPUCompiler v1.5.3
  [096a3bc2] GPUToolbox v0.2.0
  [c145ed77] GenericSchur v0.5.5
  [076d061b] HashArrayMappedTries v0.2.0
  [615f187c] IfElse v0.1.1
  [842dd82b] InlineStrings v1.4.4
  [3587e190] InverseFunctions v0.1.17
  [41ab1584] InvertedIndices v1.3.1
  [92d709cd] IrrationalConstants v0.2.4
  [82899510] IteratorInterfaceExtensions v1.0.0
  [692b3bcd] JLLWrappers v1.7.0
  [ae98c720] Jieko v0.2.1
  [63c18a36] KernelAbstractions v0.9.35
  [ba0b0d4f] Krylov v0.10.1
  [929cbde3] LLVM v9.4.2
  [8b046642] LLVMLoopInfo v1.0.0
  [b964fa9f] LaTeXStrings v1.4.0
  [10f19ff3] LayoutPointers v0.1.17
  [5078a376] LazyArrays v2.6.1
  [87fe0de2] LineSearch v0.1.4
  [d3d80556] LineSearches v7.4.0
  [7ed4a6bd] LinearSolve v3.18.2
  [2ab3a3ac] LogExpFunctions v0.3.29
  [1914dd2f] MacroTools v0.5.16
  [d125e4d3] ManualMemory v0.1.8
  [bb5d69b7] MaybeInplace v0.1.4
  [e1d29d7a] Missings v1.2.0
  [2e0e35c7] Moshi v0.3.6
  [46d2c3a1] MuladdMacro v0.2.4
  [d41bc354] NLSolversBase v7.10.0
  [5da4648a] NVTX v1.0.0
  [77ba4419] NaNMath v1.1.3
  [8913a72c] NonlinearSolve v4.9.0
  [be0214bd] NonlinearSolveBase v1.12.0
  [5959db7a] NonlinearSolveFirstOrder v1.5.0
  [9a2c21bd] NonlinearSolveQuasiNewton v1.6.0
  [26075421] NonlinearSolveSpectralMethods v1.2.0
  [bac558e1] OrderedCollections v1.8.1
  [1dea7af3] OrdinaryDiffEq v6.98.0
  [89bda076] OrdinaryDiffEqAdamsBashforthMoulton v1.2.0
  [6ad6398a] OrdinaryDiffEqBDF v1.6.0
  [bbf590c4] OrdinaryDiffEqCore v1.26.1
  [50262376] OrdinaryDiffEqDefault v1.4.0
  [4302a76b] OrdinaryDiffEqDifferentiation v1.10.0
  [9286f039] OrdinaryDiffEqExplicitRK v1.1.0
  [e0540318] OrdinaryDiffEqExponentialRK v1.4.0
  [becaefa8] OrdinaryDiffEqExtrapolation v1.5.0
  [5960d6e9] OrdinaryDiffEqFIRK v1.12.0
  [101fe9f7] OrdinaryDiffEqFeagin v1.1.0
  [d3585ca7] OrdinaryDiffEqFunctionMap v1.1.1
  [d28bc4f8] OrdinaryDiffEqHighOrderRK v1.1.0
  [9f002381] OrdinaryDiffEqIMEXMultistep v1.3.0
  [521117fe] OrdinaryDiffEqLinear v1.3.0
  [1344f307] OrdinaryDiffEqLowOrderRK v1.2.0
  [b0944070] OrdinaryDiffEqLowStorageRK v1.3.0
  [127b3ac7] OrdinaryDiffEqNonlinearSolve v1.10.0
  [c9986a66] OrdinaryDiffEqNordsieck v1.1.0
  [5dd0a6cf] OrdinaryDiffEqPDIRK v1.3.1
  [5b33eab2] OrdinaryDiffEqPRK v1.1.0
  [04162be5] OrdinaryDiffEqQPRK v1.1.0
  [af6ede74] OrdinaryDiffEqRKN v1.1.0
  [43230ef6] OrdinaryDiffEqRosenbrock v1.11.0
  [2d112036] OrdinaryDiffEqSDIRK v1.3.0
  [669c94d9] OrdinaryDiffEqSSPRK v1.3.0
  [e3e12d00] OrdinaryDiffEqStabilizedIRK v1.3.0
  [358294b1] OrdinaryDiffEqStabilizedRK v1.1.0
  [fa646aed] OrdinaryDiffEqSymplecticRK v1.3.0
  [b1df2697] OrdinaryDiffEqTsit5 v1.1.0
  [79d7bb75] OrdinaryDiffEqVerner v1.2.0
  [d96e819e] Parameters v0.12.3
  [f517fe37] Polyester v0.7.18
  [1d0040c9] PolyesterWeave v0.2.2
  [2dfb63ee] PooledArrays v1.4.3
  [d236fae5] PreallocationTools v0.4.27
⌅ [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.4.3
  [08abe8d2] PrettyTables v2.4.0
  [74087812] Random123 v1.7.1
  [e6cf234a] RandomNumbers v1.6.0
  [3cdcf5f2] RecipesBase v1.3.4
  [731186ca] RecursiveArrayTools v3.33.0
  [189a3867] Reexport v1.2.2
  [ae029012] Requires v1.3.1
  [7e49a35a] RuntimeGeneratedFunctions v0.5.15
  [94e857df] SIMDTypes v0.1.0
  [0bca4576] SciMLBase v2.102.1
  [19f34311] SciMLJacobianOperators v0.1.6
  [c0aeaf25] SciMLOperators v1.3.1
  [53ae85a6] SciMLStructures v1.7.0
  [7e506255] ScopedValues v1.3.0
  [6c6a2e73] Scratch v1.3.0
  [91c51154] SentinelArrays v1.4.8
  [efcf1570] Setfield v1.1.2
  [05bca326] SimpleDiffEq v1.12.0
  [727e6d20] SimpleNonlinearSolve v2.5.0
  [ce78b400] SimpleUnPack v1.1.0
  [a2af1166] SortingAlgorithms v1.2.1
  [0a514795] SparseMatrixColorings v0.4.21
  [276daf66] SpecialFunctions v2.5.1
  [aedffcd0] Static v1.2.0
  [0d7ed370] StaticArrayInterface v1.8.0
  [90137ffa] StaticArrays v1.9.13
  [1e83bf80] StaticArraysCore v1.4.3
  [10745b16] Statistics v1.11.1
  [7792a7ef] StrideArraysCore v0.5.7
  [892a3eda] StringManipulation v0.4.1
  [2efcf032] SymbolicIndexingInterface v0.3.41
  [3783bdb8] TableTraits v1.0.1
  [bd369af6] Tables v1.12.1
  [8290d209] ThreadingUtilities v0.5.5
  [a759f4b9] TimerOutputs v0.5.29
  [e689c965] Tracy v0.1.4
  [781d530d] TruncatedStacktraces v1.4.0
  [3a884ed6] UnPack v1.0.2
  [013be700] UnsafeAtomics v0.3.0
  [700de1a5] ZygoteRules v0.2.7
⌅ [4ee394cb] CUDA_Driver_jll v0.13.1+0
⌅ [76a88914] CUDA_Runtime_jll v0.17.1+0
  [1d5cc7b8] IntelOpenMP_jll v2025.0.4+0
  [9c1d0b0a] JuliaNVTXCallbacks_jll v0.2.1+0
  [dad2f222] LLVMExtra_jll v0.0.37+2
  [ad6e5548] LibTracyClient_jll v0.9.1+6
  [856f044c] MKL_jll v2025.0.1+1
  [e98f9f5b] NVTX_jll v3.2.1+0
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
  [1e29f10c] demumble_jll v1.3.0+0
  [1317d2d5] oneTBB_jll v2022.0.0+0
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [ade2ca70] Dates v1.11.0
  [8ba89e20] Distributed v1.11.0
  [f43a241f] Downloads v1.6.0
  [7b1f6079] FileWatching v1.11.0
  [9fa8497b] Future v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [4af54fe1] LazyArtifacts v1.11.0
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.11.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.11.0
  [de0858da] Printf v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization v1.11.0
  [6462fe0b] Sockets v1.11.0
  [2f01184e] SparseArrays v1.11.0
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.1.1+0
  [deac9b47] LibCURL_jll v8.6.0+0
  [e37daf67] LibGit2_jll v1.7.2+0
  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.6+0
  [14a3606d] MozillaCACerts_jll v2023.12.12
  [4536629a] OpenBLAS_jll v0.3.27+1
  [05823500] OpenLibm_jll v0.8.5+0
  [bea87d4a] SuiteSparse_jll v7.7.0+0
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.11.0+0
  [8e850ede] nghttp2_jll v1.59.0+0
  [3f19e933] p7zip_jll v17.4.0+2
Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`
```

  - Output of `versioninfo()`

```julia
Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 16 × AMD Ryzen 7 7840HS w/ Radeon 780M Graphics
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver4)
Threads: 8 default, 0 interactive, 4 GC (on 16 virtual cores)
Environment:
  JULIA_REVISE_WORKER_ONLY = 1
```

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Batch solve failed for problems with decreasing intervals #352

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