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

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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Bibliographic Details
Main Authors: Muhammad Ahmed, Sardar Usman, Nehad Ali Shah, M. Usman Ashraf, Ahmed Mohammed Alghamdi, Adel A. Bahadded, Khalid Ali Almarhabi
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Applied Sciences
Subjects:
sparse matrices
artificial intelligence
machine learning
compressed sparse row (CSR)
block CSR
decision trees
Online Access:https://www.mdpi.com/2076-3417/12/14/7073

Internet

https://www.mdpi.com/2076-3417/12/14/7073

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