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Aproximaciones Orientadas al Hardware de Softmax y RMSNorm para una Inferencia Eficiente de Transformers
Yiwen Kang1,2, Dong Wang1,2
1Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China.
Este estudio presenta métodos eficientes en hardware para acelerar la inferencia de Transformers optimizando operadores no lineales como Softmax y RMSNorm. Estas técnicas reducen los costos de recursos y la latencia mientras mantienen la precisión del modelo para modelos de lenguaje grandes (LLMs).
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