[GH-ISSUE #252] About the concept of channel in DeepEP and NCCL #187

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opened 2026-10-26 09:56:11 +00:00 by bsakaguchi · 1 comment
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Originally created by @lucky0218 on GitHub (Jun 24, 2025).
Original GitHub issue: https://github.com/deepseek-ai/DeepEP/issues/252

I'm confused about the concept of ​​‘channels’​​ used in both DeepEP and NCCL. Why do we isolate communication resources using channels? In other words, why not configure a single large channel to handle all data transfers by allocating more resources to it?

What specific ​​resource isolation​​ exists between different channels? What benefits do channels provide?

Additionally, why doesn’t the ​​LL (Low Latency) mode​​ require channel partitioning?

Any clarification you could provide on these points would be incredibly helpful for my understanding. Thank you for your time on the project.

Originally created by @lucky0218 on GitHub (Jun 24, 2025). Original GitHub issue: https://github.com/deepseek-ai/DeepEP/issues/252 I'm confused about the concept of ​​‘channels’​​ used in both DeepEP and NCCL. Why do we isolate communication resources using channels? In other words, why not configure a single large channel to handle all data transfers by allocating more resources to it? What specific ​​resource isolation​​ exists between different channels? What benefits do channels provide? Additionally, why doesn’t the ​​LL (Low Latency) mode​​ require channel partitioning? Any clarification you could provide on these points would be incredibly helpful for my understanding. Thank you for your time on the project.
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@LyricZhao commented on GitHub (Jun 27, 2025):

In a single channel, the tokens are sent in a specific order.

If multiple SMs share the same channel, you have to do extra synchronization between SMs, which is inefficient.

<!-- gh-comment-id:3011786823 --> @LyricZhao commented on GitHub (Jun 27, 2025): In a single channel, the tokens are sent in a specific order. If multiple SMs share the same channel, you have to do extra synchronization between SMs, which is inefficient.
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deepseek-ai/DeepEP#187
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