Unverified50% confidenceFactExact time
RNN 必须按时间步顺序处理输入，无法充分利用现代 GPU 的并行计算能力，这是 Transformer 取代它的根本原因
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50%
Confidence
Long-term
Relevance
7/20/2026
First Seen
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Related Claims
UnverifiedThe Transformer was originally designed to solve the bottleneck of Recurrent Neural Networks (RNNs) being unable to perform parallel computation in machine translation tasks.75% similarUnverifiedLlama.cpp 的 -ngl 参数控制将多少 Transformer 层放到 GPU 显存中运行，若显存不足会自动将放不下的层回退到 CPU 形成混合推理模式74% similarUnverified主流Transformer架构通过KV Cache机制避免重复计算已处理的Token70% similarUnverified相比RNN/LSTM架构，Transformer支持大规模并行计算70% similarUnverified现代商用NPU执行Transformer模型推理时的能效比可达GPU的5至10倍70% similar
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