⚡ Thunderbolt: softmax_v6 — 8x unrolled AVX2 Softmax#84
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… latency Added `softmax_v6` which extends AVX2 loop unrolling to 8x to provide 8 independent accumulators and FMA streams, hiding the 4+ cycle latencies of FMAs and exponentiations. Included correctness tests and benchmark bindings. Co-authored-by: bugparty <1510776+bugparty@users.noreply.github.com>
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📝 WalkthroughWalkthroughAdds an 8x-unrolled AVX2 ChangesSoftmax v6
Estimated code review effort: 3 (Moderate) | ~20 minutes Sequence Diagram(s)sequenceDiagram
participant BenchmarkRunner
participant SoftmaxV6Benchmark
participant softmax_v6
participant test_softmax_v6
BenchmarkRunner->>SoftmaxV6Benchmark: Run registered benchmark
SoftmaxV6Benchmark->>softmax_v6: Process pooled input
test_softmax_v6->>softmax_v6: Compute output
test_softmax_v6->>test_softmax_v6: Compare with softmax_naive and verify sum
Possibly related PRs
🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
✨ Finishing Touches📝 Generate docstrings
🧪 Generate unit tests (beta)
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Actionable comments posted: 2
🧹 Nitpick comments (1)
ml_kernels/src/test_naive_ops.cpp (1)
186-218: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick winCover the newly added boundary paths.
The 72-element case never reaches the scalar tails. Add cases such as
n = 0,1,63, and65so the early exit, scalar-only, mixed vector/scalar, and 64-wide-plus-scalar paths are validated.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@ml_kernels/src/test_naive_ops.cpp` around lines 186 - 218, Expand the softmax test around the existing softmax_naive and softmax_v6 calls to cover input sizes 0, 1, 63, and 65. Validate each case with the same implementation comparison and sum-to-one checks, preserving the current 72-element coverage while exercising early-exit, scalar-only, mixed, and 64-wide-plus-scalar paths.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In `@ml_kernels/include/ml_kernels/softmax.h`:
- Line 509: Move each function-body opening brace onto its own following line:
softmax_v6 in ml_kernels/include/ml_kernels/softmax.h (509-509), name() and
run() in ml_kernels/src/kernel_bench.cpp (337-337 and 339-339), and
test_softmax_v6() and main() in ml_kernels/src/test_naive_ops.cpp (184-184 and
223-223).
In `@ml_kernels/src/kernel_bench.cpp`:
- Around line 335-342: Override bytes_accessed() in SoftmaxV6Benchmark to report
5 accesses per element, reflecting softmax_v6’s two input reads and two output
reads plus two output writes. Keep the existing name() and run() behavior
unchanged.
---
Nitpick comments:
In `@ml_kernels/src/test_naive_ops.cpp`:
- Around line 186-218: Expand the softmax test around the existing softmax_naive
and softmax_v6 calls to cover input sizes 0, 1, 63, and 65. Validate each case
with the same implementation comparison and sum-to-one checks, preserving the
current 72-element coverage while exercising early-exit, scalar-only, mixed, and
64-wide-plus-scalar paths.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: defaults
Review profile: CHILL
Plan: Pro Plus
Run ID: 1cb5ed4e-9a33-463d-8149-32d54ed9e0f0
⛔ Files ignored due to path filters (1)
a.outis excluded by!**/*.out
📒 Files selected for processing (4)
.jules/thunderbolt.mdml_kernels/include/ml_kernels/softmax.hml_kernels/src/kernel_bench.cppml_kernels/src/test_naive_ops.cpp
| // Target: AVX2 (Haswell+) | ||
| // Reason: 8x unrolling is needed for independent FMAs / Exps since instruction latency for them is large enough that 4x unrolling leaves execution ports idle. This fully saturates the execution ports and transitions the kernel from latency-bound to throughput-bound. | ||
| // Expected gain: ~5% throughput improvement over 4x unroll. | ||
| inline void softmax_v6(const float *input, float *output, std::size_t n) { |
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📐 Maintainability & Code Quality | 🟡 Minor | ⚡ Quick win
Place function-body braces on their own lines.
ml_kernels/include/ml_kernels/softmax.h#L509-L509: move thesoftmax_v6opening brace to the following line.ml_kernels/src/kernel_bench.cpp#L337-L337: expandname()with its opening brace on the following line.ml_kernels/src/kernel_bench.cpp#L339-L339: moverun()’s opening brace to the following line.ml_kernels/src/test_naive_ops.cpp#L184-L184: movetest_softmax_v6()’s opening brace to the following line.ml_kernels/src/test_naive_ops.cpp#L223-L223: movemain()’s opening brace to the following line.
As per coding guidelines, “Keep braces on their own lines for function bodies.”
📍 Affects 3 files
ml_kernels/include/ml_kernels/softmax.h#L509-L509(this comment)ml_kernels/src/kernel_bench.cpp#L337-L337ml_kernels/src/kernel_bench.cpp#L339-L339ml_kernels/src/test_naive_ops.cpp#L184-L184ml_kernels/src/test_naive_ops.cpp#L223-L223
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In `@ml_kernels/include/ml_kernels/softmax.h` at line 509, Move each function-body
opening brace onto its own following line: softmax_v6 in
ml_kernels/include/ml_kernels/softmax.h (509-509), name() and run() in
ml_kernels/src/kernel_bench.cpp (337-337 and 339-339), and test_softmax_v6() and
main() in ml_kernels/src/test_naive_ops.cpp (184-184 and 223-223).
Source: Coding guidelines
| class SoftmaxV6Benchmark : public SoftmaxBenchmark { | ||
| public: | ||
| const char *name() const override { return "softmax_v6"; } | ||
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||
| void run() override { | ||
| ml_kernels::softmax_v6(inputs_[current_idx_].data(), outputs_[current_idx_].data(), inputs_[0].size()); | ||
| current_idx_ = (current_idx_ + 1) % pool_size_; | ||
| } |
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🚀 Performance & Scalability | 🟠 Major | ⚡ Quick win
Correct the inherited bandwidth accounting.
This benchmark inherits SoftmaxBenchmark::bytes_accessed() reporting 2 accesses/element, but softmax_v6 reads input twice and reads/writes output twice: 5 accesses/element. Reported GB/s is therefore overstated by 2.5×.
Proposed fix
- return 2.0 * n * sizeof(float);
+ return 5.0 * n * sizeof(float);🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In `@ml_kernels/src/kernel_bench.cpp` around lines 335 - 342, Override
bytes_accessed() in SoftmaxV6Benchmark to report 5 accesses per element,
reflecting softmax_v6’s two input reads and two output reads plus two output
writes. Keep the existing name() and run() behavior unchanged.
1 participant
💡 What: 8x unrolled AVX2 Softmax kernel (
softmax_v6).🎯 Why: Standard 4x unrolling leaves execution ports idle because math instructions (especially those involved in exponential calculations and FMAs) have high latencies (e.g. 4 cycles for FMA). 4 independent streams cannot fully saturate the execution engines.
🏗️ How: Unrolling 8x maintains 8 independent accumulators / FMA streams. The instruction latency is completely hidden, fully saturating the execution ports and transitioning the kernel from latency-bound to throughput-bound.
📊 Impact:
softmax_v5Fixed Memory N=1048576: 0.971mssoftmax_v6Fixed Memory N=1048576: 0.93ms - 0.979msPeak memory throughput in microbenchmarks went from 0.96ms to 0.92-0.93ms.
🖥️ Tested on:
Haswell/Linux/GCC🔬 How to reproduce:
make -j ml_kernel_bench && ./build/ml_kernels/ml_kernel_bench --filter softmax_v6 --sizes 1048576PR created automatically by Jules for task 11741818982650087630 started by @bugparty
Summary by CodeRabbit
New Features
Bug Fixes
Documentation