feat(exp,simd): adding experimental SIMD operators

[samber]

Min,Max,Sum,Clamp,ReduceSum,ReduceMin,ReduceMax

See #231

poke @d-enk

[claude]

Claude finished @samber's task in 2m 3s —— View job

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SIMD PR Review

• Read implementation files
• Review documentation structure
• Check for bugs/issues
• Verify against contribution guidelines
• Post findings

Code Quality

The implementation is well-structured:

• Follows ro's patterns correctly (context propagation, unsafe observables, teardown handling)
• Good CPU feature detection with caching
• Proper type parameter usage (~int8 etc. for named type support)
• Comprehensive test coverage per codecov (65.04% maintained)
• Package rename from simd to rosimd avoids import conflicts

Issues Found

1. Misleading Benchmark Summary (inline comment)

• BENCHMARK.md summary claims SIMD is faster but shows an example where it's 3-4x slower (ReduceSumUint64/xlarge)
• Consider using AddInt8/xlarge which shows actual ~1.5x speedup with AVX-512

2. CI Workflow License Step (test.simd.yml:36-40)

• Already noted - references non-existent paths (ee/fixtures/license/...)
• This will cause CI to fail

3. Documentation Issues (already noted in previous reviews)

• Stray # in docs/docs/plugins/exp-simd.md:14
• Missing fmt imports in doc examples

Performance Notes

SIMD shows mixed results:

• Add/Sub: ~1.5x faster on large datasets with AVX-512
• Reduce operations: Often slower due to scalar conversion overhead
• The scalar↔vector conversion API adds overhead that may offset SIMD gains

Overall

Solid implementation. Main concerns:

1. Fix the CI workflow (remove license prep step)
2. Update benchmark summary to reflect reality or use a better example
3. Address the documentation formatting issues (already noted)

[Copilot]

Pull request overview

This PR adds experimental SIMD (Single Instruction Multiple Data) operators to the ro reactive observables library, leveraging Go 1.26's experimental SIMD support for high-performance data processing on AMD64 processors.

Changes:

• Implements SIMD-accelerated operators: Add, Sub, Min, Max, Clamp, ReduceSum, ReduceMin, ReduceMax
• Supports SSE (128-bit), AVX2 (256-bit), and AVX-512 (512-bit) instruction sets with automatic CPU feature detection
• Adds conversion operators for transforming between scalar and SIMD vector types
• Includes comprehensive test suite and benchmarks for all variants
• Provides extensive documentation in README and docs/ directory

Reviewed changes

Copilot reviewed 30 out of 36 changed files in this pull request and generated 2 comments.

Show a summary per file

File	Description
plugins/exp/simd/simd.go	Package documentation and empty file for non-AMD64 fallback
plugins/exp/simd/cpu_amd64.go	CPU feature detection (AVX, AVX2, AVX-512)
plugins/exp/simd/errors.go	Error definitions (ErrClampLowerLessThanUpper)
plugins/exp/simd/math_sse.go	SSE math operators (128-bit vectors)
plugins/exp/simd/math_avx2.go	AVX2 math operators (256-bit vectors)
plugins/exp/simd/math_avx512.go	AVX-512 math operators (512-bit vectors)
plugins/exp/simd/conversion_sse.go	SSE scalar/vector conversion operators
plugins/exp/simd/conversion_avx2.go	AVX2 scalar/vector conversion operators
plugins/exp/simd/conversion_avx512.go	AVX-512 scalar/vector conversion operators
plugins/exp/simd/*_test.go	Comprehensive test suites for all implementations
plugins/exp/simd/go.mod	Module definition requiring Go 1.26
plugins/exp/simd/README.md	Detailed package documentation with usage examples
docs/data/plugin-simd-*.md	Documentation for each SIMD operator
docs/docs/plugins/exp-simd.md	Plugin overview documentation
go.work	Updated workspace to Go 1.26 and added simd plugin
README.md	Added SIMD plugin to plugin list
.github/workflows/test.simd.yml	CI workflow for SIMD tests

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[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 65.04%. Comparing base (1a3a9be) to head (b5335c7).

Additional details and impacted files

@@           Coverage Diff           @@
##             main     #232   +/-   ##
=======================================
  Coverage   65.04%   65.04%           
=======================================
  Files          95       95           
  Lines        9104     9104           
=======================================
  Hits         5922     5922           
  Misses       3088     3088           
  Partials       94       94           

Flag	Coverage Δ
unittests	65.04% <ø> (ø)

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