
Zhicheng Wu enhanced inter-node data transfer performance and dispatch reliability in the deepseek-ai/DeepEP repository by optimizing kernel communication and addressing stability issues. He allocated one RDMA queue pair per streaming multiprocessor, updating channel ID calculations to support more queue pairs and improve throughput for large-scale deployments. Using C++ and CUDA, he fixed a race condition in the dispatch logic by restricting certain operations to a single warp, reducing redundant sends and improving reliability. His work focused on distributed systems and high-performance computing, laying a maintainable foundation for future scaling and performance improvements in DeepEP’s internode communication infrastructure.

June 2025 – DeepEP (deepseek-ai/DeepEP): Enhanced inter-node data transfer performance and dispatch reliability with targeted optimizations and a key stability fix. This month focused on optimizing inter-node kernel communication and eliminating race conditions that could impact throughput on large-scale deployments.
June 2025 – DeepEP (deepseek-ai/DeepEP): Enhanced inter-node data transfer performance and dispatch reliability with targeted optimizations and a key stability fix. This month focused on optimizing inter-node kernel communication and eliminating race conditions that could impact throughput on large-scale deployments.
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