[Refactor] Treat local.var as local buffers when deciding vectorization for stable actions#1835
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📝 WalkthroughWalkthroughThe PR modifies buffer locality detection in the tile operation lowering pass to treat var-mapped buffers as local, and adds a test case verifying vectorization behavior with var buffers during parallel execution. Changes
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Actionable comments posted: 1
🤖 Fix all issues with AI agents
In `@testing/python/language/test_tilelang_language_parallel.py`:
- Around line 69-77: The test uses the low-level T.parallel() in
_parallel_vectorize_local_and_var while other tests use the TileLang high-level
T.Parallel(); update the for loop in _parallel_vectorize_local_and_var to use
T.Parallel() instead of T.parallel() so the file remains consistent with the
TileLang API (search for the function _parallel_vectorize_local_and_var and
replace the T.parallel(...) usage with T.Parallel(...)).
🧹 Nitpick comments (1)
testing/python/language/test_tilelang_language_parallel.py (1)
79-82: Consider adding a CUDA-availability guard.Other tests in this file skip gracefully when CUDA is unavailable (
_require_cuda_tensor). Ifget_kernel_source()requires a CUDA-capable environment for compilation, this test will hard-fail in CPU-only CI. Consider wrapping it with a skip check similar to the other tests.
| @tilelang.jit | ||
| def _parallel_vectorize_local_and_var(): | ||
| with T.Kernel(1) as _: | ||
| x = T.alloc_fragment([256], T.float32) | ||
| y = T.alloc_fragment([256], T.float32) | ||
| z = T.alloc_var(T.float32) | ||
| for i in T.parallel(256): | ||
| y[i] = x[i] * z | ||
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🧩 Analysis chain
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# First, find and read the test file to verify the actual casing
fd test_tilelang_language_parallel.py --type fRepository: tile-ai/tilelang
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if [ -f "testing/python/language/test_tilelang_language_parallel.py" ]; then
echo "=== Lines 69-77 (the disputed code) ===" && \
sed -n '69,77p' testing/python/language/test_tilelang_language_parallel.py && \
echo -e "\n=== Lines 18, 33, 36 (for comparison) ===" && \
sed -n '18p;33p;36p' testing/python/language/test_tilelang_language_parallel.py
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Use T.Parallel() for consistency with the rest of the file.
Line 75 uses T.parallel() (the low-level TVM IR API), while lines 18, 33, and 36 use T.Parallel() (the TileLang high-level API). Both are valid, but the file should use T.Parallel() consistently for readability and to maintain the TileLang abstraction level.
🤖 Prompt for AI Agents
In `@testing/python/language/test_tilelang_language_parallel.py` around lines 69 -
77, The test uses the low-level T.parallel() in
_parallel_vectorize_local_and_var while other tests use the TileLang high-level
T.Parallel(); update the for loop in _parallel_vectorize_local_and_var to use
T.Parallel() instead of T.parallel() so the file remains consistent with the
TileLang API (search for the function _parallel_vectorize_local_and_var and
replace the T.parallel(...) usage with T.Parallel(...)).
Performance Regression Test ReportTriggered by: @LeiWang1999 Results
Artifacts
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1 participant
Summary by CodeRabbit
Refactor
Tests