docs: standardize VAE Parallel naming
Signed-off-by: Hongsheng Liu <liuhongsheng4@huawei.com>
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@@ -10,7 +10,7 @@ This guide covers the parallelism methods in vLLM-Omni for speeding up diffusion
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| **[Sequence Parallelism](sequence_parallel.md)** | Splits sequence dimension across GPUs (Ulysses-SP, Ring-Attention, or hybrid) for high-resolution images and videos |
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| **[CFG-Parallel](cfg_parallel.md)** | Runs CFG positive/negative branches on separate GPUs for ~1.8x speedup on guided generation |
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| **[Pipeline Parallelism](pipeline_parallel.md)** | Splits the denoising transformer block-wise across sequential GPU stages to reduce per-GPU model memory |
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| **[VAE Parallelism](vae_parallel.md)** | Distributes VAE decode spatially across GPUs to reduce peak VAE memory |
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| **[VAE Parallel](vae_parallel.md)** | Distributes VAE decode spatially across GPUs to reduce peak VAE memory |
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| **[HSDP](hsdp.md)** | Shards full model weights via PyTorch FSDP2 to enable large-model inference on memory-constrained GPUs |
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| **[Expert Parallelism](expert_parallel.md)** | Shards MoE expert blocks across GPUs for MoE models (e.g. HunyuanImage3.0) |
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# VAE Parallelism Guide
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# VAE Parallel Guide
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## Table of Content
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