DeepSeek's official open-source sparse-attention TopK and sampling CUDA kernels directly determine DSA inference compute and memory costs, so any team reproducing or deploying the model needs them. Official backing could make it a de facto standard absorbed by frameworks like vLLM, though it only fits their own architecture.
DeepSelect: TopK kernels for DeepSeek Sparse Attention (DSA) and Samplers
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