
FlashMLA:突破Transformer瓶颈,下一代高效注意力机制引擎
FlashMLA is an optimized algorithm for Multi-Head Attention that dramatically improves inference performance through streaming chunking, online normalization, and register-level pipelining, reducing memory usage and increasing speed while maintaining numerical stability. FlashMLA通过分块计算、在线归一化和寄存器级流水线等优化技术,显著提升多头注意力计算性能,在降低内存消耗的同时提高速度并保持数值稳定性。
AI大模型2026/1/23
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