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AAQAL: A Machine Learning-Based Tool for Performance Optimization of Parallel SPMV Computations Using Block CSR

The sparse matrix–vector product (SpMV), considered one of the seven dwarfs (numerical methods of significance), is essential in high-performance real-world scientific and analytical applications requiring solution of large sparse linear equation systems, where SpMV is a key computing operation. As...

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Egile Nagusiak: Muhammad Ahmed, Sardar Usman, Nehad Ali Shah, M. Usman Ashraf, Ahmed Mohammed Alghamdi, Adel A. Bahadded, Khalid Ali Almarhabi
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: MDPI AG 2022-07-01
Saila:Applied Sciences
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Sarrera elektronikoa:https://www.mdpi.com/2076-3417/12/14/7073
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