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Fix grammatical error in strategy description.
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@@ -2,7 +2,7 @@
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When using expert parallelism (EP), different experts are assigned to different GPUs. Because the load of different
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When using expert parallelism (EP), different experts are assigned to different GPUs. Because the load of different
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experts may vary depending on the current workload, it is important to keep the load of different GPUs balanced.
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experts may vary depending on the current workload, it is important to keep the load of different GPUs balanced.
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As described in the DeepSeek-V3 paper, we adopt **redundant experts** strategy that duplicates heavy-loaded experts.
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As described in the DeepSeek-V3 paper, we adopt a **redundant experts** strategy that duplicates heavy-loaded experts.
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Then, we heuristically pack the duplicated experts to GPUs to ensure load balancing across different GPUs. Moreover,
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Then, we heuristically pack the duplicated experts to GPUs to ensure load balancing across different GPUs. Moreover,
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thanks to the **group-limited expert routing** used in DeepSeek-V3, we also attempt to place the experts of the same
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thanks to the **group-limited expert routing** used in DeepSeek-V3, we also attempt to place the experts of the same
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group to the same node to reduce inter-node data traffic, whenever possible.
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group to the same node to reduce inter-node data traffic, whenever possible.
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