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v0.7.0 - Performance Learning Framework Integration

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@OldCrow OldCrow released this 02 Aug 04:21
· 141 commits to main since this release
v0.7.0
b743304

This release delivers a performance learning framework that automatically optimizes execution strategy selection based on real-world performance measurements.

🎯 Performance Learning Framework:

  • Intelligent auto-dispatch with confidence-based recommendations
  • Adaptive threshold learning from actual execution data
  • 5-strategy optimization (SCALAR → SIMD → PARALLEL → WORK_STEALING → CACHE_AWARE)
  • Thread-safe learning system with atomic operations

🛠️ Complete Tool Suite:

  • Interactive learning demos with real confidence metrics
  • Comprehensive hardware capability analysis
  • Exhaustive performance benchmarking with CSV export
  • Strategy selection analysis across all distributions

⚡ Smart Auto-Dispatch API:

  • getProbability(span, span, hint) methods for all distributions
  • Automatic strategy selection based on problem characteristics
  • Performance hints for advanced optimization control
  • Full backward compatibility maintained

✅ Production Quality:

  • All tests passing with zero performance regressions
  • Sub-microsecond dispatch overhead
  • Cross-platform compatibility (macOS, Linux, Windows)
  • Comprehensive validation and confidence scoring

Ready for cross-platform testing and v0.8.0 development phase.

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