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Cambricon Unveils Full Series Model Day0 Compatibility and Open-Sourced Optimized Code for DeepSeek-V4
Cambricon has completed the "Day0" integration of DeepSeek’s latest open-source model series, DeepSeek-V4 , leveraging the vLLM inference framework. This comprehensive adaptation covers both the Flash variant (285B parameters) and the Pro variant (1.6T parameters), ensuring immediate stability on Cambricon hardware upon release. The corresponding integration code has been officially open-sourced on GitHub.
Addressing the unique sparse attention mechanisms and compressed architecture of DeepSeek-V4 , Cambricon accelerated core components like the Compressor using its proprietary vector fusion library, Torch-MLU-Ops. By utilizing the high-performance BangC language, the team developed optimized kernels for critical operations such as sparse Attention and GroupGemm. The solution fully supports five-dimensional hybrid parallelism (TP/PP/SP/DP/EP), low-precision quantization, and PD separation within the vLLM framework, significantly boosting token throughput while maintaining strict latency constraints.
On the hardware front, Cambricon exploits the memory access and sorting acceleration capabilities of MLU to manage the complex indexing structures of DeepSeek-V4 . Leveraging high interconnect bandwidth and low-latency communication, this approach minimizes overhead in Prefill and Decode phases, thereby maximizing inference efficiency.
Industry experts note that DeepSeek-V4’s million-token context window and top-tier logical reasoning capabilities demand robust underlying computing architectures. Cambricon’s rapid Day0 adaptation highlights the strength of domestic computing platforms in supporting ultra-large, complex models, signaling that the domestic AI ecosystem has reached a mature level of software-hardware synergy, providing a powerful foundation for widespread large model adoption.
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Cambricon has completed the "Day0" integration of DeepSeek’s latest open-source model series,
Addressing the unique sparse attention mechanisms and compressed architecture of
On the hardware front, Cambricon exploits the memory access and sorting acceleration capabilities of MLU to manage the complex indexing structures of
Industry experts note that DeepSeek-V4’s million-token context window and top-tier logical reasoning capabilities demand robust underlying computing architectures. Cambricon’s rapid Day0 adaptation highlights the strength of domestic computing platforms in supporting ultra-large, complex models, signaling that the domestic AI ecosystem has reached a mature level of software-hardware synergy, providing a powerful foundation for widespread large model adoption.
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