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[GH-ISSUE #50] Why NUM_MAX_NVL_PEERS must be 8? #48
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Originally created by @Huixxi on GitHub (Mar 6, 2025).
Original GitHub issue: https://github.com/deepseek-ai/DeepEP/issues/50
In deep_ep.hpp, Can it be a smaller number? For example I only have a node with 2 H800 to run test_low_latency.py
@LyricZhao commented on GitHub (Mar 6, 2025):
If you only have one node, EP2 is supported for both intranode kernels (via NVLink) and low-latency kernels (via RDMA).
For multiple nodes with each less than 8 GPUs, you can change the
NUM_MAX_NVL_PEERSmacro into your settings to see whether the kernels work. We may later add a compilation macro for this. Thanks for feedback.@alokprasad commented on GitHub (Nov 3, 2025):
Related issue https://github.com/deepseek-ai/DeepEP/issues/477
@elvircrn commented on GitHub (Nov 5, 2025):
@LyricZhao Hitting this assert when switching NUM_MAX_NVL_PEERS to 4:
@annali07 commented on GitHub (Nov 10, 2025):
Encountered the same issue.
And when I attempt to resolve by commenting out the assertions, I get a new error:
/miniconda3/envs/sglang/lib/python3.10/site-packages/deep_ep/buffer.py", line 135, in __init__ self.runtime.sync(device_ids, ipc_handles, root_unique_id) RuntimeError: Failed: CUDA error /home/annali/sglang/DeepEP/csrc/deep_ep.cpp:113 'invalid resource handle'I'm on the latest branch of DeepEP with NUM_MAX_NVL_PEERS=2
@jgcb00 commented on GitHub (Feb 2, 2026):
Same problem here, did anyone found a solution ?