Qwen3.5

Qwen3.5 Inference Performance Engineering on Hygon DCU: From Prefill/Decode Hotspots to End-to-End Gains

Qwen3.5 Inference Performance Engineering on Hygon DCU: From Prefill/Decode Hotspots to End-to-End Gains

Created|Project|Hygon DCU•Qwen3.5•vLLM•Prefill•Decode•Performance Analysis
AbstractIn large-model inference optimization, one of the easiest things to misinterpret is treating a local speedup of a certain kernel directly as an improvement in service throughput. Even if a kernel is 1.08x faster in isolated tests, the complete service may be only a few percent faster, or ...
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Hygon DCU Long-Context Attention: From page784 to page832
Hygon DCU Long-Context Attention: From page784 to page832
Qwen3.5 Inference Performance Engineering on Hygon DCU: From Prefill/Decode Hotspots to End-to-End Gains
Qwen3.5 Inference Performance Engineering on Hygon DCU: From Prefill/Decode Hotspots to End-to-End Gains
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THU-BDC2026 Experiment Log - Those Optimizations That Made the Results Worse and Worse
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