[Diffusion] Document runtime cache hardware tradeoffs
Signed-off-by: Hongsheng Liu <liuhongsheng4@huawei.com>
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@@ -110,6 +110,14 @@ independent `TP=2` engines normally create two entries: both TP0 workers map
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one entry and both TP1 workers map the other. Cache sharing does not create a
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process group or an inference-time collective.
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At inference time, cached tensors remain pageable mmap views. DLO packs each
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streamed block into one of two bounded pinned host slots before the asynchronous
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H2D copy. The private ordinary-loader path instead creates model-sized pinned
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storage once during initialization. The cache therefore exchanges recurrent
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host-to-host copies and DDR bandwidth for lower steady-state PSS; competing TP
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ranks or engines can turn staging skew into collective wait time. Treat this as
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a host-capacity mode and benchmark it on the target CPU/memory topology.
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The mmap plan skips only dedicated DiT weight sources. Other component sources,
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such as a text encoder loaded through the shared diffusion loader, continue to
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use their ordinary component loader. A checkpoint source that mixes DiT and
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@@ -207,5 +215,13 @@ loads private weights before remapping, and validation adds full content-hash
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passes. Skip-load-on-cache-hit and cache eviction remain follow-up work in
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[RFC #6195](https://github.com/vllm-project/vllm-omni/issues/6195).
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It is also not latency-neutral. In the four-L20X MiniMax-H3 smoke documented in
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the L20X runtime-cache matrix in the
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[feature design](../../../design/feature/offloader/distributed_layerwise_offload.md#l20x-runtime-cache-smoke-matrix),
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two independent TP2 engines reduced request-time host PSS by 36.6% with the
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cache, but recurrent mmap-to-pinned staging reduced combined throughput by
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69.3%. HBM and GPU compute were unchanged. Use the cache only when that
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measured memory/latency tradeoff is appropriate for the deployment.
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See the [Cosmos3 DistOffload recipe](https://github.com/vllm-project/vllm-omni/blob/main/recipes/cosmos3/Cosmos3-DistOffload.md)
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for an end-to-end example.
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