Benchmark and validate sdnq attention on the local gpu: correctness
checks for mask, causal, gqa and padding code paths, float8 support
probe, per-shape speed and error comparison against torch sdpa and
sageattention, and measured recommendations for the settings section.
Tables fill in live with per-config compile/warmup/timing progress,
current settings are compared against recommended values, and --save
writes a plain-text transcript of the results. --config-timeout turns
stuck compiles into failed rows; sd15 skips its hadamard configs since
compiling hadamard with a non pow2 head dim currently hangs inductor.
- shape presets follow real model geometries: sd15, sdxl, anima,
flux2 klein, wan22 a14b, ltx 2.3, plus a masked joint-attention case
- runs the shipped kernel from modules/sdnq/kernels/triton_atten.py
directly, with stock sdpa restored for baselines and references
CalamitousFelicitousness
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