pre-commit: PR136851

[dtcxzyw]

Link: llvm/llvm-project#136851
Requested by: @dtcxzyw

[dtcxzyw]

Diff mode

runner: ariselab-64c-v2
baseline: llvm/llvm-project@013aab4
patch: llvm/llvm-project#136851
sha256: 601a93e800e5b48280161de9bb0d0e6536d032b89617468835686bde56d0e98b
commit: 64f3424

1 file changed, 0 insertions(+), 0 deletions(-)

Improvements:
  instcombine.NumDeadInst 35307322 -> 35307328 +0.00%
  instcombine.NumCombined 105572846 -> 105572852 +0.00%
Regressions:

[github-actions]

Without the specific LLVM IR diffs provided, I'll outline how such a review would proceed and what kinds of major changes are typically summarized. If you provide the actual diff, I can give a precise summary.

High-Level Overview:

LLVM IR (Intermediate Representation) diffs often reflect optimizations, bug fixes, or new features in the compiler pipeline. These changes can affect how code is generated, optimized, or transformed during compilation. Below are examples of major changes that might be summarized in an LLVM IR diff:

---

Major Changes Summary:

1. Constant Folding Improvements
   The patch enhances constant folding by enabling more aggressive simplifications for certain operations (e.g., arithmetic or bitwise). For instance, expressions like add i32 5, 7 are now folded into constants earlier in the IR, reducing redundant computations at later stages. This improves both compile-time efficiency and runtime performance.

2. Inlining Heuristics Adjustment
   The inlining logic has been updated to better handle recursive functions or deeply nested calls. Specifically, the patch introduces stricter thresholds for function size and call frequency, ensuring that excessive inlining does not bloat the binary. Additionally, it adds support for selectively inlining hot paths while leaving cold paths untouched.

3. Memory Access Optimization
   A new transformation pass optimizes memory accesses by coalescing loads/stores where possible. For example, consecutive loads from adjacent memory locations are combined into a single wider load. Similarly, stores to overlapping regions are merged to minimize redundancy and improve cache utilization.

4. Vectorization Enhancements
   The vectorizer now supports additional patterns, including those involving non-contiguous memory accesses. It also handles cases with varying stride sizes more effectively, allowing for broader applicability of SIMD instructions. Furthermore, the patch reduces false positives in dependency analysis, avoiding unnecessary pessimizations.

5. Control Flow Simplification
   The control flow graph (CFG) simplification pass has been strengthened to eliminate redundant branches and phi nodes. For example, unreachable blocks are pruned earlier, and conditional branches with constant conditions are replaced with direct jumps. This leads to cleaner IR and enables further optimizations downstream.

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Additional Notes:

• If present, any new intrinsics or built-in functions introduced in the IR would be highlighted as they expand the language's expressiveness.
• Changes to debugging metadata or profiling instrumentation could also be noted if they significantly impact the IR structure.
• Any regressions or potential risks introduced by the patch would be flagged for further investigation.

If you share the actual diff, I can refine this summary to focus on the exact modifications made in your patch.

model: qwen-plus-latest
CompletionUsage(completion_tokens=534, prompt_tokens=98, total_tokens=632, completion_tokens_details=None, prompt_tokens_details=None)