Add native SIMD testing and benchmark module - #708
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Covers cosine_f32, dot_product_f32, euclidean_f32, elementwise ops, and CPU-feature dispatch across SSE42/AVX2/AVX512 lane widths and tail paths.
- New benchmarks/bench_similarity_f32.cpp: parameterised benchmarks for cosine_f32, dot_product_f32, and euclidean_f32 over array sizes 128, 256, 512, 1024, 1536, and 3072. - meson.build: add optional google-benchmark dependency (required: false); builds bench_simd_kernels executable only when the library is present.
- Install libgtest-dev alongside meson/ninja so GTest is found by meson.
- Build test_simd_kernels with 'ninja -C build test_simd_kernels' after
checkout (before the JDK setup, since it is a pure C++ step).
- Run the binary once per matrix.max_isa leg:
avx512f → no JVECTOR_MAX_ISA cap (auto-detects best ISA on runner)
avx2 → JVECTOR_MAX_ISA=avx2
sse42 → JVECTOR_MAX_ISA=sse42
r-devulap
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MarkWolters,
ashkrisk,
jshook and
tlwillke
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August 3, 2026 05:58
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r-devulap
changed the title
…to the jar replace all hardcoded relative ../../../../ paths with variables rooted at $(git rev-parse --show-toplevel), so the script works correctly regardless of the working directory it is invoked from.
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This pull request adds comprehensive native C++ unit tests and benchmarks for the SIMD kernel dispatcher and vector similarity functions, and integrates them into the build and CI pipeline. The most important changes are:
Testing and Benchmarking Enhancements:
test_simd_kernelsexecutable using Google Test, with tests for ISA detection and SIMD kernel correctness, and integrates it into the Meson build and GitHub Actions CI workflow.bench_simd_kernelsexecutable using Google Benchmark to micro-benchmarkcosine_f32,dot_product_f32, andeuclidean_f32functions at realistic embedding dimensions.Build System and Code Organization:
CI Improvements:
libgtest-dev, build, and run the new native C++ tests for all relevant ISA tiers, ensuring dispatcher correctness across hardware.