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Offloading strategies for Stencil kernels on the KNC Xeon Phi architecture: Accuracy versus performance

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Offloading strategies for Stencil kernels on the KNC Xeon Phi architecture: Accuracy versus performance

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Hernández, M.; Cebrián, JM.; Cecilia-Canales, JM.; García, JM. (2020). Offloading strategies for Stencil kernels on the KNC Xeon Phi architecture: Accuracy versus performance. International Journal of High Performance Computing Applications. 34(2):199-297. https://doi.org/10.1177/1094342017738352

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/169425

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Title: Offloading strategies for Stencil kernels on the KNC Xeon Phi architecture: Accuracy versus performance
Author: Hernández, Mario Cebrián, Juan M. Cecilia-Canales, José María García, José M.
UPV Unit: Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Issued date:
Abstract:
[EN] The ever-increasing computational requirements of HPC and service provider applications are becoming a great challenge for hardware and software designers. These requirements are reaching levels where the isolated ...[+]
Subjects: Offloading computation , Stencil codes , Approximate computing , Heterogeneous computing
Copyrigths: Reserva de todos los derechos
Source:
International Journal of High Performance Computing Applications. (issn: 1094-3420 )
DOI: 10.1177/1094342017738352
Publisher:
SAGE Publications
Publisher version: https://doi.org/10.1177/1094342017738352
Project ID:
info:eu-repo/grantAgreement/f SéNeCa//15290%2FPI%2F10/ES/Diseño, evaluación y explotación de aplicaciones biomédicas para arquitecturas paralelas de altas prestaciones y bajo coste/
...[+]
info:eu-repo/grantAgreement/f SéNeCa//15290%2FPI%2F10/ES/Diseño, evaluación y explotación de aplicaciones biomédicas para arquitecturas paralelas de altas prestaciones y bajo coste/
info:eu-repo/grantAgreement/UAGro//UAGro-197/
info:eu-repo/grantAgreement/f SéNeCa//18946%2FJLI%2F13/
info:eu-repo/grantAgreement/MINECO//TIN2016-78799-P/ES/DESARROLLO HOLISTICO DE APLICACIONES EMERGENTES EN SISTEMAS HETEROGENEOS/
info:eu-repo/grantAgreement/MINECO//TIN2015-66972-C5-3-R/ES/TECNICAS PARA LA MEJORA DE LAS PRESTACIONES, FIABILIDAD Y CONSUMO DE ENERGIA DE LOS SERVIDORES. OPTIMIZACION DE APLICACIONES CIENTIFICAS, MEDICAS Y DE VISION ARTIFICIAL/
info:eu-repo/grantAgreement/AEI//RYC-2018-025580-I/
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Thanks:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work is jointly supported by the Fundacion Seneca (Agencia Regional de Ciencia y ...[+]
Type: Artículo

References

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Michael Brown, W., Carrillo, J.-M. Y., Gavhane, N., Thakkar, F. M., & Plimpton, S. J. (2015). Optimizing legacy molecular dynamics software with directive-based offload. Computer Physics Communications, 195, 95-101. doi:10.1016/j.cpc.2015.05.004

Esmaeilzadeh, H., Blem, E., St. Amant, R., Sankaralingam, K., & Burger, D. (2012). Power Limitations and Dark Silicon Challenge the Future of Multicore. ACM Transactions on Computer Systems, 30(3), 1-27. doi:10.1145/2324876.2324879

Feng, L. (2015). Data Transfer Using the Intel COI Library. High Performance Parallelism Pearls, 341-348. doi:10.1016/b978-0-12-802118-7.00020-0

Jeffers, J., & Reinders, J. (2013). Offload. Intel Xeon Phi Coprocessor High Performance Programming, 189-241. doi:10.1016/b978-0-12-410414-3.00007-4

Rahman, R. (2013). Intel® Xeon Phi™ Coprocessor Architecture and Tools. doi:10.1007/978-1-4302-5927-5

Reinders J, Jeffers J (2014) High Performance Parallelism Pearls, Multicore and Many-core Programming Approaches (Characterization and Auto-tuning of 3DFD). Morgan Kaufmann, pp. 377–396.

Shareef, B., de Doncker, E., & Kapenga, J. (2015). Monte Carlo simulations on Intel Xeon Phi: Offload and native mode. 2015 IEEE High Performance Extreme Computing Conference (HPEC). doi:10.1109/hpec.2015.7322456

Ujaldón, M. (2016). CUDA Achievements and GPU Challenges Ahead. Lecture Notes in Computer Science, 207-217. doi:10.1007/978-3-319-41778-3_20

Wang, E., Zhang, Q., Shen, B., Zhang, G., Lu, X., Wu, Q., & Wang, Y. (2014). High-Performance Computing on the Intel® Xeon Phi™. doi:10.1007/978-3-319-06486-4

Wende, F., Klemm, M., Steinke, T., & Reinefeld, A. (2015). Concurrent Kernel Offloading. High Performance Parallelism Pearls, 201-223. doi:10.1016/b978-0-12-802118-7.00012-1

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