⚡ Thunderbolt: Softmax - Hybrid 8x/4x unrolling for memory passes - #91
⚡ Thunderbolt: Softmax - Hybrid 8x/4x unrolling for memory passes#91bugparty wants to merge 1 commit into
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- Implements `softmax_v6` in `ml_kernels/include/ml_kernels/softmax.h` utilizing a hybrid unrolling strategy. The max-finding (Pass 1) and normalization (Pass 3) passes are unrolled 8x to saturate execution ports and memory bandwidth by hiding the `_mm256_max_ps` 4-cycle latency. The exponential computation (Pass 2) remains unrolled 4x to avoid high register pressure and spilling. - Adds `SoftmaxV6Benchmark` to `kernel_bench.cpp`. - Adds `test_softmax_v6` in `test_naive_ops.cpp` and invokes it in `main` using an array of 72 elements to effectively test boundary element accumulation. - Records micro-architectural learning in `.jules/thunderbolt.md` reflecting that multi-pass kernel loop unrolling should be independently tuned according to whether the individual pass is latency-bound or throughput-bound. - Yields a measured throughput gain of ~13.3% on large out-of-cache fixed memory arrays (`N=1048576`), improving from ~3.22 GFLOP/s to ~3.65 GFLOP/s on the test system. Co-authored-by: bugparty <1510776+bugparty@users.noreply.github.com>
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📝 WalkthroughWalkthroughAdded ChangesSoftmax V6
Estimated code review effort: 3 (Moderate) | ~20 minutes Sequence Diagram(s)sequenceDiagram
participant BenchmarkOrTest
participant softmax_v6
participant exp256_ps_v2
participant Output
BenchmarkOrTest->>softmax_v6: Process input values
softmax_v6->>softmax_v6: Find maximum with 8-way unrolling
softmax_v6->>exp256_ps_v2: Compute exponentials with 4-way unrolling
exp256_ps_v2-->>softmax_v6: Return exponent values
softmax_v6->>Output: Normalize with 8-way unrolling
Output-->>BenchmarkOrTest: Return softmax results
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)
196-215: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick winCover scalar tails and exact transition sizes.
The 72-element case covers a 64-element block plus an 8-element vector remainder. It does not execute the 1-7 element scalar tails or isolate the 32- and 64-element boundaries. Run the same oracle for sizes 1, 7, 8, 31, 32, 33, 63, 64, and 65.
Proposed test extension
assert(std::fabs(sum - 1.0f) < 1e-4f); + for (std::size_t size : {1U, 7U, 8U, 31U, 32U, 33U, 63U, 64U, 65U}) { + std::vector<float> case_input(input.begin(), input.begin() + size); + std::vector<float> case_naive(size); + std::vector<float> case_v6(size); + + ml_kernels::softmax_naive(case_input.data(), case_naive.data(), size); + ml_kernels::softmax_v6(case_input.data(), case_v6.data(), size); + + float case_sum = 0.0f; + for (std::size_t i = 0; i < size; ++i) { + assert(std::fabs(case_naive[i] - case_v6[i]) < 1e-4f); + case_sum += case_v6[i]; + } + assert(std::fabs(case_sum - 1.0f) < 1e-4f); + } + std::cout << "test_softmax_v6 passed!" << std::endl;🤖 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 196 - 215, Extend the softmax test around the existing oracle in the test case containing output_naive and output_v6 to run sizes 1, 7, 8, 31, 32, 33, 63, 64, and 65. For each size, construct an input of that exact length, invoke softmax_naive and softmax_v6, and retain both element-wise agreement and sum-to-one assertions so scalar tails and 32/64-element transition boundaries are covered.
🤖 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`:
- Around line 507-510: Revise the comments at
ml_kernels/include/ml_kernels/softmax.h lines 507-510 and .jules/thunderbolt.md
line 32 to separate pass-specific rationale: state that Pass 1’s independent
accumulators hide _mm256_max_ps latency, while justifying Pass 3’s 8x unrolling
only through measured load/store bandwidth or multiply throughput; do not
attribute max latency hiding to Pass 3.
- Line 512: Update the softmax_v6 function declaration so its opening brace
appears on the following line, while leaving the function signature and body
unchanged.
---
Nitpick comments:
In `@ml_kernels/src/test_naive_ops.cpp`:
- Around line 196-215: Extend the softmax test around the existing oracle in the
test case containing output_naive and output_v6 to run sizes 1, 7, 8, 31, 32,
33, 63, 64, and 65. For each size, construct an input of that exact length,
invoke softmax_naive and softmax_v6, and retain both element-wise agreement and
sum-to-one assertions so scalar tails and 32/64-element transition boundaries
are covered.
🪄 Autofix
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: 2aa8479e-d2c6-4bcb-9a90-4909fc6dec89
📒 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
| // Reason: Multi-pass memory-bound kernels like Softmax benefit from 8x unrolling in the memory-bound passes (Max and Normalize) | ||
| // to fully saturate memory bandwidth and hide the 4-cycle `_mm256_max_ps` latency. | ||
| // However, unrolling the FMA-heavy exponentiation pass (Pass 2) 8x causes register spilling and port saturation. | ||
| // A hybrid approach (Pass 1: 8x, Pass 2: 4x, Pass 3: 8x) optimally balances execution resources. |
There was a problem hiding this comment.
📐 Maintainability & Code Quality | 🟡 Minor | ⚡ Quick win
Separate the max-pass latency rationale from normalization tuning.
Pass 3 does not execute _mm256_max_ps. Do not state that its 8x unroll hides _mm256_max_ps latency. State that Pass 1 uses independent accumulators to hide max latency. Justify Pass 3 unrolling with measured load/store bandwidth or multiply throughput.
ml_kernels/include/ml_kernels/softmax.h#L507-L510: revise the implementation comment to limit_mm256_max_pslatency hiding to Pass 1..jules/thunderbolt.md#L32-L32: revise the journal entry to use the same pass-specific rationale.
📍 Affects 2 files
ml_kernels/include/ml_kernels/softmax.h#L507-L510(this comment).jules/thunderbolt.md#L32-L32
🤖 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` around lines 507 - 510, Revise the
comments at ml_kernels/include/ml_kernels/softmax.h lines 507-510 and
.jules/thunderbolt.md line 32 to separate pass-specific rationale: state that
Pass 1’s independent accumulators hide _mm256_max_ps latency, while justifying
Pass 3’s 8x unrolling only through measured load/store bandwidth or multiply
throughput; do not attribute max latency hiding to Pass 3.
| // However, unrolling the FMA-heavy exponentiation pass (Pass 2) 8x causes register spilling and port saturation. | ||
| // A hybrid approach (Pass 1: 8x, Pass 2: 4x, Pass 3: 8x) optimally balances execution resources. | ||
| // Expected gain: ~5-10% throughput improvement over softmax_v5 on large arrays. | ||
| inline void softmax_v6(const float *input, float *output, std::size_t n) { |
There was a problem hiding this comment.
📐 Maintainability & Code Quality | 🟠 Major | ⚡ Quick win
Put the function opening brace on a separate line.
Line 512 places the function opening brace on the declaration line. Move it to its own line.
Proposed fix
-inline void softmax_v6(const float *input, float *output, std::size_t n) {
+inline void softmax_v6(const float *input, float *output, std::size_t n)
+{As per coding guidelines, **/*.{c,cpp,cc,h,hpp} requires: “Keep braces on their own lines for function bodies.”
📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| inline void softmax_v6(const float *input, float *output, std::size_t n) { | |
| inline void softmax_v6(const float *input, float *output, std::size_t n) | |
| { |
🤖 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 512, Update the softmax_v6
function declaration so its opening brace appears on the following line, while
leaving the function signature and body unchanged.
Source: Coding guidelines
1 participant
Implement AVX2 Softmax (
softmax_v6) with a hybrid unrolling strategy. Max-finding and normalization loops are unrolled 8x to hide the 4-cycle latency of_mm256_max_ps, while the exponential FMA loop is unrolled 4x to limit register spilling. Throughput increased by ~13% on large out-of-cache configurations. Added correctness testing, benchmarks, and a new learning entry to Thunderbolt journal.PR created automatically by Jules for task 10662953882600623064 started by @bugparty
Summary by CodeRabbit
New Features
Bug Fixes
Documentation