implementation detail · filed under inference & serving
Fused QSA kernel
A kernel that jointly computes sparse-attention outputs and KL loss without materializing intermediate results.
Also called Fused sparse-attention and KL-loss kernel.
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Evidence
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we implement a fused QSA kernel that jointly computes sparse attention outputs and the KL loss without materializing intermediate results
usedunclearin Qwen3.8-Flash-NextQwen
Filed alongside
Other methods under inference & serving :: inference kernel.
Batch-invariant deterministic kernelsCUDA GraphCUDA Graph capture size reductionFlashAttention 3Kernel fusionMoE-side chunkingSynchronization-free static-shape MoE executionTensorRT-LLM multi-head attention backendAvoiding split-KDeepGEMM-based batch-invariant matrix multiplicationDistributed shared memory for cross-SM attention data exchangeDual-kernel batch-invariant attention decodingDynamic load balancingExp-free TopK kernelExpert-optimized Triton kernelsFA4 sheared-bias attention kernelFlashAttentionFlashAttention 4FlashKDAFP8 GEMMFused AttnRes merge and RMSNorm kernelFused latent down-projection and MoE-router GEMMFused mHC kernelsFused RoPE-attention-RoPE-cast kernel