Files
hao-ai-lab-FastVideo/docs
Aryan KumarandClaude Opus 5.5 1c1aa75f33 [perf]: faster FastH3 decode and NVFP4 GEMMs in the DGX Spark recipes
On GB10 the light H3 VAE's INT8 ConvRot overlay decodes 832x480x124 in
42 s and gains nothing from tile batching. The dense weights take 24 s
with one tile per decoder call, 14 s with 12 tiles per call and 9.8 s
compiled, at higher fidelity (77.7 vs 63.4 dB PSNR against an FP32
decode). FASTVIDEO_H3_VAE_INT8_OVERLAY=0 now skips the overlay (default
on, so other recipes are unchanged), and the single-Spark recipes use it
with FASTVIDEO_H3_VAE_TILE_BATCH=12 and a compiled VAE decoder.

FlashInfer's CUTLASS mm_fp4 is 2.7-3x slower than its cuDNN backend for
the H3 FFN projections on GB10 with identical outputs, so the recipes
select FASTVIDEO_NVFP4_MM_BACKEND=cudnn. FlashInfer autotuning was not
adopted: it made repeated calls non-deterministic.

One Spark, 832x480x124, seed 1234, warm calls: FastH3 Trim 121-122 s to
68 s (denoise 78 -> 58 s, decode 43 -> 9.5 s); FastH3 V2 139-141 s to
79 s. Repeated calls are bit-identical, which the previous V2 recipe was
not.

FP4 attention (FASTVIDEO_H3_VSA_FP4=1, built for sm_121a since #1598) is
documented for GB10 as opt-in and stays off: it is 24-33% faster in
denoise on V2 but changes the output (LPIPS 0.39-0.55 against BF16
attention), and the checkpoints were not trained for it.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-09 11:43:20 -07:00
..
2026-07-19 18:37:47 -07:00

FastVideo Documentation

This directory contains the FastVideo documentation built with MkDocs.

Build the docs locally

# Install dependencies
uv pip install -r requirements-mkdocs.txt

# Serve docs with live reload (recommended for development)
mkdocs serve

# Or build static site
mkdocs build

View the docs

Development server (with live reload)

mkdocs serve

Then open your browser to: http://127.0.0.1:8000

Static build

mkdocs build
python -m http.server -d site/

Then open your browser to: http://localhost:8000

Automatic Deployment

Documentation is automatically built and deployed to GitHub Pages when changes are pushed to the main branch via the .github/workflows/infra-docs.yml workflow.

Update documentation dependencies

Edit requirements-mkdocs.in, then regenerate the pinned Linux/Python 3.12 lock file:

uv pip compile requirements-mkdocs.in \
  -o requirements-mkdocs.txt \
  --python-platform x86_64-manylinux_2_28 \
  --python-version 3.12