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[GH-ISSUE #1999] [Bug]: test_mooncake_ep.py failed #556
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kvcache-ai/Mooncake#556
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Originally created by @zbnlala on GitHub (Apr 28, 2026).
Original GitHub issue: https://github.com/kvcache-ai/Mooncake/issues/1999
Originally assigned to: @UNIDY2002 on GitHub.
Bug Report
I installed Mooncake v0.3.10.post1 by:
However when i run test_mooncake_ep.py ,it fails sometimes as shown below:
Is there something wrong with my settings? All other tests are running normally.
Before submitting...
@UNIDY2002 commented on GitHub (Apr 28, 2026):
Hi @zbnlala! Can you share your GPU model and the NIC model? Thanks!
@zbnlala commented on GitHub (Apr 28, 2026):
GPUs are L20
@zbnlala commented on GitHub (May 8, 2026):
@UNIDY2002 hi,any progress?
@UNIDY2002 commented on GitHub (May 8, 2026):
The problem may be related to PCIe P2P. Would you please try whether commenting out these lines will help?
github.com/kvcache-ai/Mooncake@5ba016ac1c/mooncake-wheel/mooncake/mooncake_ep_buffer.py (L180-L203)@zbnlala commented on GitHub (May 8, 2026):
@UNIDY2002 Thank you! After commenting it out, there won't be any more bugs. However, I’m still wondering whether this indicates an issue with my environment or configuration. And will commenting it out have any impact on the functionality of mooncake-ep?
@UNIDY2002 commented on GitHub (May 8, 2026):
That part was for NVLink, so since your environment does not involve NVLink (correct me if I'm wrong), it will not have a negative impact. However, I will add an environment variable flag so that you will not have to manually comment out the unrelated code.
@zbnlala commented on GitHub (May 8, 2026):
@UNIDY2002 hi, I have another question related to SGLang + Mooncake-ep. When starting SGLang, I used the following command:
There is error:
I printed the
ScheduleBatch, and it seems that the error occurs whenever a batch in theidlestate is being processed.I also tried setting
self._use_fallback = Truein the buffer so that I could trace into theself._fallback_dispatch()function. The error then appeared at the following line with the same failure:Interestingly, if I change device=x.device to device="cpu", this line can execute successfully, but the same error appears again at the next GPU-related operation. This makes me suspect that the issue may be related to GPU blocking. Do you have any suggestions on how to debug or resolve this?
@UNIDY2002 commented on GitHub (May 9, 2026):
I haven't yet allocated enough resource to reproduce this case, but I have a clue: there are several conditionals missing for models other than DeepSeek V3. Would you try adding some conditions in the qwen3 model file just like in the following commit (although it was for qwen2)?
github.com/HanHan009527/sglang@bf6488fb52@zbnlala commented on GitHub (May 11, 2026):
@UNIDY2002 It works!I have replaced all
get_moe_a2a_backend().is_deepep()inqwen2_moe.pyandqwen3_moe.pywith(get_moe_a2a_backend().is_deepep() or get_moe_a2a_backend().is_mooncake()), The service can proceed normally.Thanks for answering!