localmem does not work for cpu backend?

Hi, I am trying to write a matvec kernel with shared memory, it works for CUDA backend. However, it results in an error when switched to CPU backend:

```
ERROR: LoadError: UndefVarError: `j` not defined in `Main`
Stacktrace:
[1] cpu_matvec_kernel!
```

How to fix it? many thanks.

The julia script is shown below:
```julia
using KernelAbstractions
using CUDA
using Test

@kernel function matvec_kernel!(output, @Const(A), @Const(b))
I = @index(Global, Linear)
I = div(I-1, 32) + 1
idx = @index(Local, Linear)
i = (idx - 1) % 32 + 1 #local index within the wrap

cache_size = @uniform @groupsize()
cache = @localmem eltype(output) cache_size

N = size(A, 2)
sum = zero(eltype(output))
@inbounds begin
for J = i:32:N
sum += A[I, J] * b[J]
end
cache[idx] = sum
end
@synchronize

j::Int = 16
while j > 0
if i <= j
@inbounds cache[idx] += cache[idx + j] # can not find j for cpu backend
end
@synchronize
j = j ÷ 2
end

if i == 1
@inbounds output[I] = cache[idx]
end

end

function matvec!(output, A, b)
backend = KernelAbstractions.get_backend(A)
kernel! = matvec_kernel!(backend, 256)
kernel!(output, A, b; ndrange=32*size(A, 1))
end

m, n = 2^10, 2^10
A = CUDA.rand(Float32, m, n)
b = CUDA.rand(Float32, n)
output = CUDA.rand(Float32, m)

matvec!(output, A, b)
@test isapprox(output, A * b)

matvec!(Array(output), Array(A), Array(b))
```

The versioninfo() gives:

```
julia> versioninfo()
Julia Version 1.11.1
Commit 8f5b7ca12a (2024-10-16 10:53 UTC)
Build Info:
Official https://julialang.org/ release
Platform Info:
OS: Windows (x86_64-w64-mingw32)
CPU: 24 × 13th Gen Intel(R) Core(TM) i7-13700F
WORD_SIZE: 64
LLVM: libLLVM-16.0.6 (ORCJIT, alderlake)
Threads: 1 default, 0 interactive, 1 GC (on 24 virtual cores)

julia> CUDA.versioninfo()
CUDA runtime 12.6, artifact installation
CUDA driver 12.6
NVIDIA driver 561.3.0

CUDA libraries:
- CUBLAS: 12.6.3
- CURAND: 10.3.7
- CUFFT: 11.3.0
- CUSOLVER: 11.7.1
- CUSPARSE: 12.5.4
- CUPTI: 2024.3.2 (API 24.0.0)
- NVML: 12.0.0+561.3

Julia packages:
- CUDA: 5.5.2
- CUDA_Driver_jll: 0.10.3+0
- CUDA_Runtime_jll: 0.15.3+0

Toolchain:
- Julia: 1.11.1
- LLVM: 16.0.6

1 device:
0: NVIDIA GeForce RTX 3060 Ti (sm_86, 5.048 GiB / 8.000 GiB available)
```

Start with the provided matvec_kernel! reproducer and compare its CUDA and CPU executions, focusing on the @localmem usage and the CPU backend path. The issue is resolved when the CPU invocation runs without the UndefVarError and the resulting output passes the existing isapprox check.

Written by the indexing model from the issue text.