Add comprehensive rustynum vs ndarray comparison with benchmarks#1
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Cross-reference comparison document covering features, architecture, API, and performance benchmarks between ndarray and rustynum. See AdaWorldAPI/rustynum for the full benchmark harness. https://claude.ai/code/session_01EHNZhSmJ52FGyDxtCFgzXo
AdaWorldAPI
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Mar 23, 2026
#1 VML wiring: Wire F32x16/F64x8 SIMD types into scalar VML loops - vsln: 16-wide via simd_ln_f32 - vdsqrt: 8-wide via F64x8::sqrt() - vdabs: 8-wide via F64x8::abs() - vssin/vscos: batch load/store via F32x16 (scalar per-lane, SIMD framework) - vspow: 16-wide via exp(b*ln(a)) using simd_exp_f32 + simd_ln_f32 - 7 new tests covering SIMD paths #5 columnar_view: Zero-copy Arrow interop - SoakingBuffer::as_columnar_slice() / as_columnar_slice_mut() - PlaneBuffer::as_binary_slice() - 3 new tests for zero-copy view correctness #6 simd_apply: Generic fused SIMD kernel - simd_apply(a, b, out, Fn(F32x16, F32x16) -> F32x16) - simd_apply_unary(x, out, Fn(F32x16) -> F32x16) - simd_apply_inplace(a, b, Fn(F32x16, F32x16) -> F32x16) - Proper tail handling via zero-padded SIMD - 6 new tests (add, FMA, sqrt, inplace, empty, tail-only) #10 prefetch: Explicit _mm_prefetch in cascade_query - prefetch_t0/t1 wrappers (x86_64 SSE, no-op elsewhere) - Stroke 1: prefetch PREFETCH_DISTANCE=4 candidates ahead (L1) - Stroke 2: prefetch next survivor's data (L2) - Stroke 3: prefetch next survivor's data (L1) All 51 targeted tests pass. Scorecard: 4/10 → 6/10 done. https://claude.ai/code/session_01CdqyUTUfjKZuk8YGJzv6LB
AdaWorldAPI
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Mar 30, 2026
Tactics 1-12 from the 34-tactic integration plan, adapted to ndarray: styles::rte — #1 Recursive Thought Expansion (Hofstadter) styles::htd — #2 Hierarchical Thought Decomposition (CLAM) styles::smad — #3 Structured Multi-Agent Debate (NARS revision) styles::tcp — #5 Thought Chain Pruning (Berry-Esseen) styles::irs — #9 Iterative Roleplay Synthesis (XOR binding) styles::mcp — #10 Meta-Cognition (Brier score calibration) styles::tca — #12 Temporal Context (Reichenbach tense) Plus additions to existing modules: causal_diff.rs — #4 reverse_trace() (Pearl Rung 3) bgz17_bridge.rs — #6 inject_noise() (simulated annealing) nars.rs — #7 adversarial_critique(), #11 detect_contradiction() cascade.rs — #8 adaptive_resolution() Every tactic is fn(Base17, NarsTruth) → result. No LLM prompting. 16 tests passing. API: crate::hpc::styles::rte::expand() etc. https://claude.ai/code/session_01M3at4EuHVvQ8S95mSnKgtK
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Cross-reference comparison document covering features, architecture, API, and performance benchmarks between ndarray and rustynum. See AdaWorldAPI/rustynum for the full benchmark harness.
https://claude.ai/code/session_01EHNZhSmJ52FGyDxtCFgzXo