Add blog post on oneAPI v1.5.

post/2024-05-24-oneapi_1.5.md

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+title = "oneAPI.jl 1.5: Ponte Vecchio support and oneMKL improvements"
+author = "Tim Besard"
+external = true
+abstract = """
+  oneAPI.jl v1.5 is a significant release that brings many new features, from extended
+  hardware support to greatly improved wrappers of the oneMLK math library."""
++++
+
+{{abstract}}
+
+
+## Intel Ponte Vecchio
+
+In oneAPI.jl v1.5 we introduce support for the Intel Ponte Vecchio (PVC) architecture,
+which empowers the Xe HPC GPUs as found in the Aurora supercomputer:
+
+```julia-repl
+julia> oneAPI.versioninfo()
+Binary dependencies:
+- NEO: 24.13.29138+0
+- libigc: 1.0.16510+0
+- gmmlib: 22.3.18+0
+- SPIRV_LLVM_Translator_unified: 0.4.0+0
+- SPIRV_Tools: 2023.2.0+0
+
+Toolchain:
+- Julia: 1.10.3
+- LLVM: 15.0.7
+
+1 driver:
+- 00000000-0000-0000-17d2-6b1e010371d2 (v1.3.29138, API v1.3.0)
+
+16 devices:
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+- Intel(R) Data Center GPU Max 1550
+```
+
+Apart from [a handful of MKL-related
+issues](https://github.com/JuliaGPU/oneAPI.jl/issues/428), oneAPI.jl is fully functional on
+PVC, and passes all tests.
+
+
+## oneMLK wrappers
+
+Thanks to the work of [@amontoison](https://github.com/amontoison), oneAPI.jl now provides
+greatly improved wrappers of the oneMKL library. This includes support for:
+
+- LAPACK: `geqrf`(`_batched`), `orgqr`(`_batched`), `ormqr`, `potrf`(`_batched`),
+          `potrs`(`_batched`), `getrf`(`_batched`), `getri`(`_batched`), `gebrd`, `gesvd`,
+          `syevd`, `heevd`, `sygvd`, `hegvd`
+- Sparse arrays: `sparse_gemm`, `sparse_gemv`, `sparse_symv`, `sparse_trmv`, `sparse_trsv`,
+                 `sparse_optimize_gemv`, `sparse_optimize_trsv`
+
+Where possible, these functions are integrated with standard library interfaces, e.g.,
+making it possible to simply call `eigen`, or to multiply two `oneSparseMatrixCSR`s.
+
+
+## Minor changes
+
+There have of course been many other changes and improvements in oneAPI.jl v1.5. For a full
+list, please refer to the [release
+notes](https://github.com/JuliaGPU/oneAPI.jl/releases/tag/v1.5.0), but some highlights
+include:
+
+- a new launch configuration heuristic that should generally improve performance;
+- broadcast now preserves the buffer type (host, device, or shared);
+- support for very large arrays that exceed the default device memory limit;
+- several toolchain bumps, with v1.5 using oneAPI 2024.1.0 with driver 24.13.29138.7;
+- minimal support for native Windows (next to WSL, which is fully supported).