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Hybrid SWA–DSA architecture Network organization and the components inside a DSA attention module A Network stack Tokens → Embedding Typical hybrid group SWA : DSA = 5 : 1 SWA block 1 Local attention + FFN SWA block 2 Local attention + FFN SWA block 3 Local attention + FFN SWA block 4 Local attention + FFN SWA block 5 Local attention + FFN DSA block Sparse attention + FFN DSA attention is expanded in panel B → Repeat hybrid groups Final RMSNorm LM head Vocabulary logits Schematic grouping; boundary layers omitted Legend Lightning indexer (selection path) Key DSA-specific component Main (sparse) attention path Selected top-2048 positions Residual connection B DSA attention module 1 Input 2 Project 3 Encode 4 Cache 5 Select 6 Attend 7 Output Hidden state X RMSNorm residual X Sparse attention (main heads) Lightning indexer (selects the top-2048 keys) Q projection 64 Q heads total 8 per TP rank K projection head dim = 192 V projection head dim = 128 RoPE main-attention Q RoPE main-attention K Full-history K / V cache append the current token's K and V Gather selected K / V at the indexer's top-2048 positions Q K V Q × KT selected keys only Scale + softmax P × V weighted sum Output projection Wo TP all-reduce Attention output → FFN sublayer Index Q projection Q heads = 16 head dim = 128 Weight projection 16 head weights Index K projection K heads = 1 head dim = 128 RoPE FP8 quantization qI w[h] LayerNorm RoPE · 64D NoPE · 64D K concat → 128D along the feature axis FP8 quantization new kt Past index K cache K0 … Kt−1 Cache append [Kpast ; kt]  along time axis Index sweep over all visible keys QI · KI  →  scale  →  ReLU  →  weighted head sum Top-2048 positions one shared selection set per query selected positions Each transformer block: RMSNorm → Attention → residual add → RMSNorm → FFN → residual add The 16 indexer heads are separate from the 64 main attention heads. FFN: MoE, with a dense first-layer exception.