New version: CUDA v5.6.0

[JuliaRegistrator]

• Registering package: CUDA
• Repository: https://github.com/JuliaGPU/CUDA.jl
• Created by: @maleadt
• Version: v5.6.0
• Commit: fc952a32ff597b262dbbcdce1592e26751309eec
• Reviewed by: @maleadt
• Reference: JuliaGPU/CUDA.jl@fc952a3#commitcomment-151042129
• Description: CUDA programming in Julia.
• Release notes:

CUDA.jl v5.6 is a relatively minor release, which the most important change being behind the scenes: [GPUArrays.jl v11 has switched to KernelAbstractions.jl](https://juliagpu.org/post/2025-01-07-gpuarrays-11/) (#2524).

## Features

- Update to CUDA 12.6.2 (#2512)
- CUSOLVER: support for `Xgeev!` (#2513), `XsyevBatched` (#2577), `gesv!` and `gels!` (#2406)
- CUBLAS: added multiplication of transpose / adjoint matrices by diagonal matrices (#2518, #2538)
- Improve handle cache performance in the presence of many short-lived tasks (#2583)
- CUFFT: Pre-allocate the buffer required for complex-to-real FFTs only once (#2578)
- Improved batched pointer conversion for very large batches (#2608)

## Bug fixes

- Fix `findall` with an empty CuArray (#2554)
- CUBLAS: Fix use of level 1 methods with strided arrays (#2528)
- CUSOLVER: Fix `Xgesvdr!` (#2556)
- Preserve the array buffer type with more linear algebra operations (#2534)
Work around LinearAlgebra.jl breakage in Julia 1.11.2 concerning generic triangular `(l/r)mul!` - (#2585)
- Fix ambiguity of `LinearAlgebra.dot` (#2569)
- Native RNG: Fixes when working with very large arrays (#2561)
- Avoid a deadlock due do union splitting in the `mapreduce` kernel (#2595)
- Fix pinning of resized CPU memory by automatically re-pinning (#2599)

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