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[Minor] update docs (#14212)

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Lianmin Zheng
2025-12-01 02:33:58 -08:00
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docs/advanced_features/hicache_design.md
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@@ -99,7 +99,7 @@ However, because GPU KV computation is naturally performed layer by layer, the G
### Integration with PD-Disaggregation Deployment Mode
SGLang supports a PD (Prefill-Decode) disaggregation deployment mode through the Mooncake TransferEngine (for details, see [this doc](https://docs.sglang.ai/advanced_features/pd_disaggregation.html)). In the PD-disaggregation deployment mode, HiCache can be enabled on both the prefill nodes and decode nodes to optimize prefill performance. If enabled on decode nodes, the decode output will also be written back to L3.
SGLang supports a PD (Prefill-Decode) disaggregation deployment mode through the Mooncake TransferEngine (for details, see [this doc](https://docs.sglang.io/advanced_features/pd_disaggregation.html)). In the PD-disaggregation deployment mode, HiCache can be enabled on both the prefill nodes and decode nodes to optimize prefill performance. If enabled on decode nodes, the decode output will also be written back to L3.
### Unified Interfaces and Rich L3 Storage Backends