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Micro-kernels for portable and efficient matrix multiplication in deep learning

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Micro-kernels for portable and efficient matrix multiplication in deep learning

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Alaejos-López, G.; Castelló, A.; Martínez, H.; Alonso-Jordá, P.; Igual, FD.; Quintana-Ortí, ES. (2023). Micro-kernels for portable and efficient matrix multiplication in deep learning. The Journal of Supercomputing. 79:8124-8147. https://doi.org/10.1007/s11227-022-05003-3

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Título: Micro-kernels for portable and efficient matrix multiplication in deep learning
Autor: Alaejos-López, Guillermo Castelló, Adrián Martínez, Héctor Alonso-Jordá, Pedro Igual, Francisco D. Quintana-Ortí, Enrique S.
Entidad UPV: Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica
Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Fecha difusión:
Resumen:
[EN] We provide a practical demonstration that it is possible to systematically generate a variety of high-performance micro-kernels for the general matrix multiplication (gemm) via generic templates which can be easily ...[+]
Palabras clave: Matrix multiplication , Linear algebra libraries , High performance , Vector intrinsics , SIMD units
Derechos de uso: Reconocimiento (by)
Fuente:
The Journal of Supercomputing. (issn: 0920-8542 )
DOI: 10.1007/s11227-022-05003-3
Editorial:
Springer-Verlag
Versión del editor: https://doi.org/10.1007/s11227-022-05003-3
Código del Proyecto:
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113656RB-C22/ES/COMPUTACION Y COMUNICACIONES DE ALTAS PRESTACIONES CONSCIENTES DEL CONSUMO ENERGETICO. APLICACIONES AL APRENDIZAJE PROFUNDO COMPUTACIONAL - UPV/
...[+]
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113656RB-C22/ES/COMPUTACION Y COMUNICACIONES DE ALTAS PRESTACIONES CONSCIENTES DEL CONSUMO ENERGETICO. APLICACIONES AL APRENDIZAJE PROFUNDO COMPUTACIONAL - UPV/
info:eu-repo/grantAgreement/CAM//PR65%2F19-22445/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-093684-B-I00/ES/HETEROGENEIDAD Y ESPECIALIZACION EN LA ERA POST-MOORE/
info:eu-repo/grantAgreement/CAM//S2018%2FTCS-4423 /
info:eu-repo/grantAgreement/MCIU//FJC2019-039222-I/
info:eu-repo/grantAgreement/AEI//PID2021-126576NB-I00/
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Agradecimientos:
Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was supported by the research projects PID2020-113656RB-C22, RTI2018-093684-B-I00, and PID2021-126576NB-I00, of MCIN/AEI/10.1 ...[+]
Tipo: Artículo

References

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