InvalidIRError: Reason: unsupported dynamic function invocation (call to print_to_string(xs...)

Hi,

when I run the code below on the CPU everything works as expected.
When trying to run it on the GPU, I get the error:

ERROR: LoadError: InvalidIRError: compiling kernel gpu_get_segment_indices_kernel!(KernelAbstractions.CompilerMetadata{KernelAbstractions.NDIteration.StaticSize{(3, 10)}, KernelAbstractions.NDIteration.DynamicCheck, Nothing, Nothing, KernelAbstractions.NDIteration.NDRange{2, KernelAbstractions.NDIteration.StaticSize{(1, 10)}, KernelAbstractions.NDIteration.StaticSize{(16, 1)}, Nothing, Nothing}}, CuDeviceMatrix{CartesianIndex{2}, 1}, CuDeviceMatrix{Float32, 1}, CuDeviceMatrix{Float32, 1}) resulted in invalid LLVM IR
Reason: unsupported dynamic function invocation (call to print_to_string(xs...) in Base at strings/io.jl:133)

Any ideas?
Maybe related to https://github.com/JuliaGPU/KernelAbstractions.jl/issues/286

The code:

using CUDA
using CUDAKernels
using KernelAbstractions

@kernel function get_segment_indices_kernel!(result, @Const(x), @Const(knots))
    I = @index(Global, NTuple)
    variable_index = I[1:end - 1]

    result[I...] = CartesianIndex(
        clamp(
            searchsortedlast(knots[:, variable_index...], x[I...]),
            firstindex(knots, 1),
            lastindex(knots, 1) - 1,
        ),
        variable_index...,
    )

    nothing
end

function get_segment_indices(x, knots)
    kernel_device = begin
        if x isa CuArray
            CUDADevice()
        else
            CPU()
        end
    end

    indices = similar(x, eltype(CartesianIndices(x)))

    kernel = get_segment_indices_kernel!(kernel_device, 16, size(x))
    event = kernel(indices, x, knots)
    wait(event)

    indices
end


# todevice = identity
todevice = cu


n_obs = 10
n_variables = 3
n_bins = 4

x = rand(n_variables..., n_obs) |> todevice
knots = sort(rand(n_bins, n_variables...), dims=1) |> todevice

indices = get_segment_indices(x, knots)

Versions:
julia version 1.7.1
[052768ef] CUDA v3.8.3
[72cfdca4] CUDAKernels v0.4.0
[63c18a36] KernelAbstractions v0.8.0

Reproduce the GPU path in get_segment_indices_kernel! using the Julia 1.7.1, CUDA 3.8.3, CUDAKernels 0.4.0, and KernelAbstractions 0.8.0 versions listed, then compare it with the CPU path and read KernelAbstractions issue 286. Done means identifying the unsupported dynamic invocation and confirming a regression test or documented resolution for this kernel.