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[Diff since v0.9.4](https://github.com/JuliaGPU/KernelAbstractions.jl/compare/v0.9.4...v0.9.5)

**Closed issues:**
- Defining timing infrastructure that works with events. (#15)
- Kernels fail on CPU when waiting on kernels that allocate shared memory (#55)
- Use macros in nested functions (#377)
- `CPU(static=true)` option (#387)
- Need for @inline when using GPU backend (#392)
- KA seems to be broken for CUDA (#400)

**Merged pull requests:**
- Add kernel cpu=false and context accessor (#389) (@vchuravy)
- Add reverse CI for oneAPI and AMDGPU (#391) (@vchuravy)
- Update readme (#393) (@vchuravy)
- Improve clarity of numa_aware example (#397) (@carstenbauer)
- Docs: numa aware saxpy example (#398) (@carstenbauer)
- Add implementation notes to host functionality (#401) (@vchuravy)