86ca125b4766c84c16ece9bf09b89d03913854e6
CCCL block_scan_raking.cuh: parallel prefix scan over C elements using GPU-native raking threads, not sequential host-driven loops. Our _forward_sub_lower was a Python for-loop over chunk_size=64 rows, each launching a separate matmul kernel. This is 64 sequential kernel launches per DeltaNet layer per chunk. Fix: Use torch.linalg.solve_triangular (cuBLAS trsm) which solves the entire (I-A)@X=RHS system in ONE kernel launch. Falls back to the Python loop if cuSOLVER is unavailable on BI-V100. CCCL source: cub/cub/block/specializations/block_scan_raking.cuh Maps to: qwen3_6_scripts/qwen3_5.py (_forward_sub_lower)
project_6
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