⚡ Thunderbolt: softmax_v6 — 8x unroll with single-FMA exp

[bugparty]

💡 What: Added softmax_v6 kernel that simplifies exp256_ps range reduction to a single FMA and aggressively unrolls all loop phases 8x.
🎯 Why: Breaking the traditional double-FMA exact ln(2) split for range reduction into a single FMA r = x - n * ln(2) saves register pressure and instruction ports. This reduction in pressure allows the outer loops (max, exp/sum, normalize) to be unrolled 8x, handling 64 elements per iteration, which perfectly saturates out-of-order execution resources and hides execution latencies better than 4x unrolling.
🏗️ How:

• Wrote exp256_ps_single_fma using one FMA for range reduction and Horner's scheme.
• Implemented 8x unrolling in softmax_v6 for max finding, exp and sum accumulation, and normalizaton.
• Ensured careful remainder handling.
  📊 Impact:
  N=16384 (Fixed Memory): 5.63 -> 6.08 GFLOP/s (~8% gain)
  N=65536 (Fixed Memory): 5.61 -> 6.22 GFLOP/s (~10.8% gain)
  N=1048576 (Fixed Memory): 3.98 -> 4.26 GFLOP/s (~7% gain)
  🖥️ Tested on: Target CPU architecture (AVX2-capable, e.g. Haswell+)
  🔬 How to reproduce: DISABLE_CPU_BINDING=1 ./build/ml_kernels/ml_kernel_bench --filter "softmax_v5" and DISABLE_CPU_BINDING=1 ./build/ml_kernels/ml_kernel_bench --filter "softmax_v6"

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PR created automatically by Jules for task 12385161308874336821 started by @bugparty

Summary by CodeRabbit

• New Features

  • Added a faster softmax variant with improved SIMD performance and deeper loop unrolling.
  • Added a new benchmark entry to compare the latest softmax implementation against earlier versions.

• Documentation

  • Added guidance and benchmark results for the new softmax approach, including accuracy notes.

• Tests

  • Added correctness checks to verify the new softmax output stays numerically stable and sums to 1.

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No actionable comments were generated in the recent review. 🎉

ℹ️ Recent review info

⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

Plan: Pro

Run ID: 86632c09-eab9-48ce-a791-59007e77f389

📥 Commits

Reviewing files that changed from the base of the PR and between acca01e and 47dbd3a.

📒 Files selected for processing (4)

• .jules/thunderbolt.md
• ml_kernels/include/ml_kernels/softmax.h
• ml_kernels/src/kernel_bench.cpp
• ml_kernels/src/test_naive_ops.cpp

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📝 Walkthrough

Walkthrough

Adds a new AVX2 softmax kernel variant (softmax_v6) using a single-FMA exponential range-reduction helper with 8x unrolling. Includes a corresponding benchmark class, a correctness/normalization test invoked from the test suite, and a documentation entry describing the optimization.

Changes

AVX2 softmax_v6 kernel and validation

Layer / File(s)	Summary
exp256_ps_single_fma helper and softmax_v6 kernel ml_kernels/include/ml_kernels/softmax.h	Adds exp256_ps_single_fma for single-FMA exponential range reduction and softmax_v6, an 8x-unrolled AVX2 softmax kernel performing max reduction, exp/sum accumulation, and normalization.
Benchmark, test, and documentation ml_kernels/src/kernel_bench.cpp, ml_kernels/src/test_naive_ops.cpp, .jules/thunderbolt.md	Registers SoftmaxV6Benchmark, adds test_softmax_v6 correctness/normalization checks invoked from main(), and documents the single-FMA optimization approach.

Estimated code review effort: 3 (Moderate) | ~25 minutes

Sequence Diagram(s)

sequenceDiagram
  participant Test as test_softmax_v6
  participant Kernel as softmax_v6
  participant Exp as exp256_ps_single_fma
  Test->>Kernel: call(input, output, n)
  Kernel->>Kernel: 8x unrolled max reduction
  Kernel->>Exp: compute exp per AVX vector
  Exp-->>Kernel: exponential values
  Kernel->>Kernel: accumulate sum across 8 accumulators
  Kernel->>Kernel: 8x unrolled normalize by inverse sum
  Kernel-->>Test: output array
  Test->>Test: compare against softmax_naive within tolerance

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Related Issues: None specified.

Related PRs: None specified.

Suggested labels: performance, simd, testing, documentation

Suggested reviewers: None specified.

_{🐰 A quick hop through registers eight-wide,
Single FMA folds range reduction inside,
softmax_v6 leaps past naive's slow pace,
Tests confirm the sum still lands in place.
Carrot-fueled vectors, unrolled with pride! 🥕}

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly matches the main change: the new softmax_v6 kernel with single-FMA exp and 8x unrolling.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

✨ Finishing Touches

📝 Generate docstrings

• Create stacked PR
• Commit on current branch

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch thunderbolt-softmax-v6-12385161308874336821

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