Sparse Attention

Architecture Digest

Feb 24, 2025 · Artificial Intelligence

MoBA: Mixture of Block Attention for Long‑Context Large Language Models

The article introduces MoBA, a Mixture‑of‑Block‑Attention mechanism that applies Mixture‑of‑Experts principles to transformer attention, enabling efficient long‑context processing for large language models while maintaining performance comparable to full attention through sparse, trainable block selection and seamless switching.

LLMMixture of ExpertsMoBA

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MoBA: Mixture of Block Attention for Long‑Context Large Language Models

Architects' Tech Alliance

Feb 24, 2025 · Artificial Intelligence

NSA: Hardware‑Optimized Sparse Attention Mechanism from DeepSeek, Peking University and University of Washington

The NSA mechanism introduces a three‑branch hardware‑optimized sparse attention architecture—token compression, token selection, and sliding window—combined with learnable gating to balance global and local context, dramatically improving inference speed and efficiency for long‑context large language models.

AI architectureDeepSeekLarge Language Models

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NSA: Hardware‑Optimized Sparse Attention Mechanism from DeepSeek, Peking University and University of Washington