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DeepSeek Sparse Attention (DSA) represents a sophisticated execution of this paradigm, initially deployed in DeepSeek-V3.2. To identify crucial tokens, DSA incorporates streamlined "lightning indexer modules" at each model tier. These indexing components evaluate previous tokens and curate a minimal selection for primary attention processing. This methodology reduces core attention computations from exponential to linear progression, substantially accelerating model performance while maintaining output integrity.
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