Commit Graph
5 Commits
Author SHA1 Message Date
Wenbo Ji 嵇文博 b7bd7775ed [perf] Default SM100 long-sequence Attn-QAT tiling (#1899)
On SM100, the Attn-QAT training kernel now uses a faster route for non-causal
BF16 attention with equal query and key lengths of 16384 tokens or more. The
forward pass processes full KV tiles without bounds masks, and a separate masked
step handles the partial tail tile. The backward pass uses 64x128 dQ and dK/dV
tiles. Outputs, softmax statistics and all gradients are bitwise identical to the
previous route. FASTVIDEO_ATTN_QAT_SM100_OPTIMIZED=0 turns off the SM100 route,
and FASTVIDEO_ATTN_QAT_SM100_WIDE_BWD=0 keeps the 64x64 backward tiles.

On GB200 with 6 heads and 31200 tokens, the forward kernel time goes from 9.14 ms
to 6.96 ms and the backward kernel time from 17.41 ms to 15.85 ms.
2026-10-07 15:14:38 -07:00
Yogya Mehrotra 017ce6602d [bugfix] Fix dead NVFP4 QAT plumbing: bench imports, int8 error string, smooth_q crash (#1723) 2026-09-24 17:09:33 -07:00
William Lin 9028953625 [misc] yapf pass under CI's interpreter (3.12) + pin hook language_version (#1702) 2026-08-08 22:24:17 -07:00
9709b7513b [feat] Port NVFP4 QAT/QAD to modular train framework (#1619)
Co-authored-by: Peiyuan Zhang <email>

Co-authored-by: Peiyuan <a>
2026-07-18 15:01:09 -07:00
eed9c4bfbf [kernel] QAD 5090: Add Attn-QAT training Triton kernels (11/12) (#1460)
Co-authored-by: William Lin <SolitaryThinker@users.noreply.github.com>
Co-authored-by: Loay Rashid <42599591+loaydatrain@users.noreply.github.com>
Co-authored-by: Kaiqin Kong <k1kong@ucsd.edu>
2026-06-17 13:35:12 -07:00