tilelang-cuda-synchronization

To prevent thread deadlocks in CUDA shared memory kernels, enforce safe synchronization rules by applying T.sync_threads() after all threads write to shared data, ensuring deterministic progress.

Data race conditions in TileLang CUDA kernels are caused by risky patterns like conditional synchronization and manual reductions. Using standard built-in synchronization primitives and built-in reductions prevents these data races.

You need to use T.sync_threads() in multi-thread collaboration whenever threads write to shared memory that other threads read from, establishing a safe barrier to guarantee deterministic progress and avoid stalls.

Conditional synchronization and manual reductions are not supported for TileLang CUDA kernels. You must use standard built-in reductions and memory operations to maintain correctness and avoid deadlock scenarios.

Your TileLang kernel stalls at synchronization points because conditional synchronization creates deadlock scenarios. Standardizing thread coordination with explicit T.sync_threads() prevents these stalls and guarantees deterministic progress.