A high-throughput and memory-efficient inference and serving engine for LLMs
[EP] Enable DBO with NIXL EP (#45275)
Signed-off-by: Itay Alroy <ialroy@nvidia.com>
Itay Alroy committed
Jun 16, 2026 at 02:37 UTC
3afe659b6bb90b961bf09984166393824a893af9
2 files changed
+8
-6
vllm/config/compilation.py
+1
-1
@@ -1197,7 +1197,7 @@ class CompilationConfig:
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"are optimized for prefill and are incompatible with CUDA Graphs. "
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"In order to use CUDA Graphs for decode-optimized workloads, "
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"use --all2all-backend with another option, such as "
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- "deepep_low_latency or allgather_reducescatter."
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+ "deepep_low_latency, nixl_ep, or allgather_reducescatter."
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)
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self.cudagraph_mode = CUDAGraphMode.NONE
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vllm/config/vllm.py
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-5
@@ -1457,12 +1457,14 @@ class VllmConfig:
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assert a2a_backend in [
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"deepep_low_latency",
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"deepep_high_throughput",
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+ "nixl_ep",
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], (
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- "Microbatching currently only supports the deepep_low_latency and "
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- f"deepep_high_throughput all2all backend. {a2a_backend} is not "
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- "supported. To fix use --all2all-backend=deepep_low_latency or "
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- "--all2all-backend=deepep_high_throughput and install the DeepEP"
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- " kernels."
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+ "Microbatching currently only supports the deepep_low_latency, "
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+ "deepep_high_throughput, and nixl_ep all2all backends. "
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+ f"{a2a_backend} is not supported. To fix use "
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+ "--all2all-backend=deepep_low_latency, "
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+ "--all2all-backend=deepep_high_throughput, or "
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+ "--all2all-backend=nixl_ep and install the matching kernels."
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)
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if not self.model_config.disable_cascade_attn: