C-MemMAP: clustering-driven compact, adaptable, and generalizable meta-LSTM models for memory access prediction

Please use this identifier to cite or link to this item: https://hdl.handle.net/10923/18182

Type:	Article
Title:	C-MemMAP: clustering-driven compact, adaptable, and generalizable meta-LSTM models for memory access prediction
Author(s):	Pengmiao Zhang Ajitesh Srivastava Ta-Yang Wang Cesar Augusto Fonticielha De Rose Rajgopal Kannan Viktor K. Prasanna
In:	International Journal of Data Science and Analytics
Issue Date:	2021
First page:	1
Last page:	10
Keywords:	Gerência de recursos em máquinas paralelas Escalonamento de Recursos Inteligência Artificial (IA)
URI:	https://hdl.handle.net/10923/18182
DOI:	DOI:10.1007/s41060-021-00268-y
ISSN:	2364-415X
Appears in Collections:	Artigo de Periódico

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