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[Refactor] Rename NSA → DSA: user-facing aliases, file/class/import rename (#25821)

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Co-authored-by: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Cheng Wan
2026-05-20 00:18:04 -07:00
committed by GitHub
co-authored by Claude Sonnet 4.6
parent da6d549ab2
commit 8131641bc6
162 changed files with 11298 additions and 10740 deletions
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docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_best_practice.mdx
+2 -2
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@@ -1598,8 +1598,8 @@ do
--nnodes 2 --node-rank $i \
--disaggregation-bootstrap-port 8995 \
--moe-dense-tp-size 1 \
--enable-nsa-prefill-context-parallel \
--nsa-prefill-cp-mode in-seq-split \
--enable-dsa-prefill-context-parallel \
--dsa-prefill-cp-mode in-seq-split \
--attn-cp-size 32 \
--speculative-algorithm NEXTN --speculative-num-steps 1 --speculative-eagle-topk 1 --speculative-num-draft-tokens 2 \
--dist-init-addr ${P_IP[0]}:10000
docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_environment_variables.mdx
+1 -1
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@@ -29,7 +29,7 @@ This document provides a list of commonly used environment variables and aims to
</tr>
<tr>
<td><code>SGLANG_NPU_USE_MULTI_STREAM</code></td>
<td>Enable dual-stream computation of shared experts <br/> and routing experts in DeepSeek models.<br/> Enable dual-stream computation in DeepSeek NSA Indexer.</td>
<td>Enable dual-stream computation of shared experts <br/> and routing experts in DeepSeek models.<br/> Enable dual-stream computation in DeepSeek DSA Indexer.</td>
<td><code>false</code></td>
</tr>
<tr>
docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_optimization.mdx
+6 -6
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@@ -187,18 +187,18 @@ These arguments and environment variables are critical for tuning prefill perfor
<td>true</td>
</tr>
<tr>
<td>`--enable-nsa-prefill-context-parallel`</td>
<td><strong>(DeepSeek V3.2 NSA-specific)</strong> Enables context parallelism for the long-sequence prefill phase of DeepSeek V3.2 with NSA (Native Sparse Attention). Distributes the sequence across CP ranks to parallelize the computationally expensive NSA prefill for ultra-long contexts.</td>
<td>`--enable-dsa-prefill-context-parallel`</td>
<td><strong>(DeepSeek V3.2 DSA-specific)</strong> Enables context parallelism for the long-sequence prefill phase of DeepSeek V3.2 with DSA (DeepSeek Sparse Attention). Distributes the sequence across CP ranks to parallelize the computationally expensive DSA prefill for ultra-long contexts.</td>
<td>Enabled</td>
</tr>
<tr>
<td>`--nsa-prefill-cp-mode`</td>
<td><strong>(DeepSeek V3.2 NSA-specific)</strong> Controls how the long sequence is split across context parallel ranks: `in-seq-split` divides each sequence uniformly across CP ranks, optimal for single-request prefill. `round-robin-split` (code default) distributes tokens by index mod CP size, supporting multi-batch prefill. Only effective when `--enable-nsa-prefill-context-parallel` is enabled.</td>
<td>`--dsa-prefill-cp-mode`</td>
<td><strong>(DeepSeek V3.2 DSA-specific)</strong> Controls how the long sequence is split across context parallel ranks: `in-seq-split` divides each sequence uniformly across CP ranks, optimal for single-request prefill. `round-robin-split` (code default) distributes tokens by index mod CP size, supporting multi-batch prefill. Only effective when `--enable-dsa-prefill-context-parallel` is enabled.</td>
<td>`in-seq-split`</td>
</tr>
<tr>
<td>`--attn-cp-size`</td>
<td>Specifies the context parallelism group size for attention computation. Larger values distribute the sequence across more ranks, reducing per-rank memory and compute at the cost of increased communication. For models with NSA, this controls the CP size for sparse attention prefill. Set to the number of available devices for maximum parallelization.</td>
<td>Specifies the context parallelism group size for attention computation. Larger values distribute the sequence across more ranks, reducing per-rank memory and compute at the cost of increased communication. For models with DSA, this controls the CP size for sparse attention prefill. Set to the number of available devices for maximum parallelization.</td>
<td>`32`</td>
</tr>
</tbody>
@@ -360,7 +360,7 @@ The following environment variables are used in other best practice configuratio
<tr>
<td>`HCCL_OP_EXPANSION_MODE=AIV`</td>
<td>Configures the HCCL communication algorithm scheduling to use AIV (Ascend Intelligent Vision) expansion mode, which can improve communication efficiency for certain collective operations.</td>
<td>Used in Qwen MoE and R1 non-NSA configurations</td>
<td>Used in Qwen MoE and R1 non-DSA configurations</td>
</tr>
<tr>
<td>`SGLANG_NPU_FUSED_MOE_MODE`</td>
docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_support_features.mdx
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@@ -1225,13 +1225,13 @@ click [Server Arguments](../../advanced_features/server_arguments).
<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>A2, A3</td>
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<tr>
<td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>`--nsa-prefill-backend`</td>
<td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>`--dsa-prefill-backend`</td>
<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`flashmla_sparse`</td>
<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}><code>flashmla_sparse</code>,<br/> <code>flashmla_decode</code>,<br/><code>fa3</code>,<br/> <code>tilelang</code>,<br/> <code>aiter</code></td>
<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Special for GPU</td>
</tr>
<tr>
<td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>`--nsa-decode-backend`</td>
<td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>`--dsa-decode-backend`</td>
<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`fa3`</td>
<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}><code>flashmla_prefill</code>,<br/> <code>flashmla_kv</code>,<br/> <code>fa3</code>,<br/><code>tilelang</code>,<br/> <code>aiter</code></td>
<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Special for GPU</td>
@@ -2226,7 +2226,7 @@ click [Server Arguments](../../advanced_features/server_arguments).
<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Experimental</td>
</tr>
<tr>
<td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>`--enable-nsa-prefill-`<br/>`context-parallel`</td>
<td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>`--enable-dsa-prefill-`<br/>`context-parallel`</td>
<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>`False`</td>
<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>bool flag<br/> (set to enable)</td>
<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>A2, A3</td>
docs_new/docs/hardware-platforms/plugin.mdx
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@@ -512,9 +512,9 @@ python -c "from sglang.srt.platforms import current_platform; print(current_plat
<td>MLA KV cache pool class</td>
</tr>
<tr>
<td><code>get_nsa_kv_pool_cls()</code></td>
<td><code>get_dsa_kv_pool_cls()</code></td>
<td><code>raise NotImplementedError</code></td>
<td>NSA KV cache pool class (DeepSeek V3.2)</td>
<td>DSA KV cache pool class (DeepSeek V3.2)</td>
</tr>
<tr>
<td><code>get_paged_allocator_cls()</code></td>