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SwiftRL: Towards Efficient Reinforcement Learning on Real Processing-In-Memory Systems

Fuente: arXiv

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Detalles Bibliográficos
Autores principales:	Gogineni, Kailash, Dayapule, Sai Santosh, Gómez-Luna, Juan, Gogineni, Karthikeya, Wei, Peng, Lan, Tian, Sadrosadati, Mohammad, Mutlu, Onur, Venkataramani, Guru
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence Hardware Architecture
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

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